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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Large-Scale Additive Manufacturing of Silicon Carbide with Process Monitoring

This report summarizes new capabilities in additive manufacturing (AM) of large-scale silicon carbide (SiC) components under the Advanced Materials and Manufacturing Technologies (AMMT) program. SiC is a promising material that is being considered for many advanced reactor designs due to its high temperature strength, radiation tolerance, minimal neutron absorption, and oxidation resistance [1-8]. One of the primary limitations to using SiC as an in-core structural material is the inability to fabricate large SiC components with complex geometries. While under the former Transformational Challenge Reactor (TCR) program, ceramic AM systems at the Oak Ridge National Laboratory (ORNL) were limited in the quantity and overall size achievable for producing ceramic AM components. To address this, ORNL has improved its infrastructure for binder jet and chemical vapor infiltration (CVI) processes with cutting-edge equipment coming online in a newly renovated laboratory space capable of producing larger components and higher throughput without compromise on part size. This report details the laboratory renovation progress, focusing specifically on the DesktopMetal (formerly ExOne) X25Pro binder jet, a large scale CVI furnace, and the added functionality of a software tool called Peregrine for quality assurance and control purposes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Silicon Tetrafluoride Vapor Pressure Study

The vapor pressure (VP) of silicon tetrafluoride (SiF4) was evaluated using three different cryogenic cold baths and multiple pressure transducers (PTs). Through this experiment, the known range of VP has been extended to a low temperature of 122 K. A functional relationship for the VP has been developed for the range between 122 and 159.6 K. This relationship was also used to estimate a VP value at 88 K, which was below observable levels with a 0.1 torr gauge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Can We Lower the Voltage of a Silicon Module and Still Make It Just as Efficient?

The purpose of this experiment to conserve excess amounts of energy the best I can. I am trying to lower the voltage of a machine that collects data from cosmic particles that travel through it, without greatly affecting the results. By doing this, I am effectively saving energy and also creating a more efficient silicon module.

Mason, Eddie↗
DOE OSTI2023

Development of Binder Jet Compatible Silicon Carbide Mixtures for Increased Sintered Density

Binder jet additive manufacturing can process a variety of ceramic powder feedstocks to manufacture near net shape green parts that are subsequently sintered to achieve densification. In particular, silicon carbide (SiC) is a promising ceramic material for heat exchangers in energy storage applications and binder jet is a well-suited process for manufacturing these heat exchangers due to the often geometrically complex designs. However, the need for good powder flowability in binder jet printing often limits the feedstock powder to be larger particles rather than that of ultra fine submicron powders used in conventional ceramic processing, which are more readily densified during sintering. The present work explores the use of various powder mixtures and sintering settings to identify strategies for achieving high density sintered parts in binder jet compatible systems without the use of infiltration. Liquid-phase sintering additives and bimodal powder mixtures are explored alongside different sintering temperatures, rates, atmospheres, and hold times. Two mixtures were found to be good candidates for further exploration: 1) 90 wt% 0.6 µm SiC + 6.25 wt% Al 2 O 3 + 3.75 wt% Y 2 O 3 mixture achieved the highest sintered relative density of 91.2%; and 2) a bimodal mixture comprised of 45 wt% 10 µm SiC + 45 wt% 0.6 µm SiC + 6.25 wt% Al 2 O 3 + 3.75 wt% Y 2 O 3 had the best powder flowability of the powders measured and a 75.1% sintered relative density.

25 ENERGY STORAGE↗
DOE OSTI2023

Inventory for Crystalline Silicon Module Recycling: Cooperative Research and Development (Final Report)

A critical challenge for the continued expansion of photovoltaics (PV) is to develop technically feasible, inexpensive and environmentally friendly practices for handling and recycling modules at the end of their usable life. The National Renewable Energy Laboratory (NREL) is requested by the Electric Power Research Institute (EPRI) to collect primary data regarding the environmental performance of currently operational PV module recycling facilities in Europe. Very little has been published regarding crystalline silicon (C-Si) module recycling. Thus, much effort will be needed in direct industry outreach, collection of information and other business intelligence strategies similar to NREL's approaches for developing cost models for PV manufacturing. The goal of this work effort is to produce a detailed inventory that accounts for physical (e.g., energy, water, materials) flows through each step of a C-Si recycling process. The inventory (a life cycle inventory, or LCI) shall be designed so that it can be extended to include an accounting of costs for each process step, inputs, etc. This work effort shall leverage prior LCI data collection NREL performed for the United States Department of Energy, Solar Energy Technologies Office, under the auspices of the U.S. contribution to International Energy Agency's Photovoltaics Power Systems (PVPS) Task 12 (Environmental Health and Safety), which SETO nominated NREL to chair. The primary purpose of this work effort is to augment the prior data collection to increase the sample size of manufacturers' primary data in the LCI.

14 SOLAR ENERGY↗
DOE OSTI2023

Qualification of Commercially Available Silicon Carbide for Passive Thermometry in Reactor Experiments – FY23 Status Report

Silicon carbide (SiC) is often used as a passive temperature indicator for uninstrumented in-core nuclear experiments. For the past several decades, Oak Ridge National Laboratory has relied primarily on SiC thermometry manufactured by Dow Chemical Company, formerly Rohm and Haas because of the material’s high density and reduced grain boundary elements. Although Dow SiC has performed well in this application, this material is no longer commercially available, and a new supplier is needed for future experiments. To determine a suitable replacement, a study was initiated on five types of SiC from four commercial vendors. Several critical properties, including density, electrical resistivity, chemical purity, grain structure, crystal structure, and strength were measured in samples from each material. Additionally, thermometry specimens were manufactured for irradiation in the High Flux Isotope Reactor at nominal temperatures of 300°C, 600°C, and 900°C, which will be measured using continuous dilatometry at a later date. This report provides an update of commercially available SiC material characterization and the irradiation capsule design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Characterization of Contact Degradation in Crystalline Silicon Photovoltaic Modules (Final Technical Report)

In this project, the aim was to develop highly-automated metrology methods that can provide more insights into degradation and failure, while still relying on the types of measurements the PV industry and RD communities are comfortable with (e.g., I – V and EL). In particular, our focus was to develop techniques to better understand contact and interconnect degradation in crystalline silicon (c-Si) PV modules and apply those techniques to conventional and emerging c-Si cell architectures and cell interconnection technologies.

14 SOLAR ENERGY↗
DOE OSTI2023

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2600+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6,000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with great emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with a suite of experimental data obtained from x-ray diffraction, infrared spectroscopy, spectroscopic ellipsometry and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Distributed Temperature Profiles of Silicon Carbide Catalyst Bed in a Microwave Reactor using Fiber-optic Sensor

Microwave heating is of great interest for reducing greenhouse gas emissions of catalytic chemical conversion processes because it can heat up the reactants rapidly and efficiently and accelerate reaction rates. In microwave-assisted catalytic thermochemical conversion processes, accurate internal temperature measurement would help facilitate effective process control. Metallic thermocouples interfere and spark in the microwave heating environment, so they are not an option. Infrared pyrometers typically provide a single temperature value by averaging over a finite surface area of the catalyst bed. In this work, we use fiber-optic sensors passing through the catalyst bed to provide more accurate temperatures along the height of the catalyst bed. The fiber optic sensors are immune to the electromagnetic microwave radiation and provide temperature profiles along their length. Here, custom fiber-optic sensors were coupled to the optical distributed temperature sensing devices to measure the temperature profiles along the height of the catalyst bed at high temperatures with ~1 mm spatial resolution. The sensing devices use optical frequency domain reflectometry (OFDR) technique for distributed temperature measurement. This work shows the temperature profiles along the height of the silicon carbide powder catalyst bed in the variable and fixed frequency microwave reactors.

Thapa, Juddha↗
DOE OSTI2024

Lower length scale model for palladium attack of silicon carbide in TRISO fuel

TRistructural ISOtropic (TRISO) particle fuels rely on silicon carbide (SiC) as the primary barrier for metallic fission product (FP) release. Palladium (Pd) generated by fission degrades the SiC layer, resulting in the formation of lamellar layers of palladium silicides (PdxSi) and carbon (C) perpendicular to the direction of attack. The Pd attack has been hypothesized to be responsible for failure of the SiC layer and enhance FP release. To better understand and quantify Pd attack of SiC in TRISO particles, a multiscale, mechanistic model of Pd transport is being developed by the NEAMS program. Previous work provided an initial hypothesis for modeling lamellar microstructure formation in SiC due to Pd attack using a phase-field model. The work described in this report builds on the previous model by using molecular dynamics (MD) simulations to parameterize the phase-field model kinetics, and build a reduced order model in BISON using the improved mesoscale Pd penetration model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Binder Jet Additive Manufacturing of Silicon Carbide Solar Reactor (CRADA Report)

Achieving high powder packing density is critical in binder jet additive manufacturing (BJAM), as it directly influences the final part density, mechanical properties, and sintering behavior. Multi-modal powder blends, which combine particles of different sizes, have been explored as a strategy to optimize packing efficiency and minimize defects. In this study, bimodal and trimodal powder blends were obtained by mixing silicon carbide powder in three different sizes. These results show that increased powder density is achievable with bimodal powder blends but is reduced in trimodal blends, and it was found that a 13% increase in the powder tap density was achieved using a bimodal blend of powder. The powder size distribution of the bimodal blend was measured at various stages during binder jet additive manufacturing and, no measurable powder separation occurred even after eight prints. Overall, this study shows limited advantage to trimodal powder blends but good promise for trimodal blends for increasing printed density while maintaining reusability in the binder jet process.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Binder jet additive manufacturing of silicon carbide solar reactor

Achieving high powder packing density is critical in binder jet additive manufacturing (BJAM), as it directly influences the final part density, mechanical properties, and sintering behavior. Multi-modal powder blends, which combine particles of different sizes, have been explored as a strategy to optimize packing efficiency and minimize defects. In this study, bimodal and trimodal powder blends were obtained by mixing silicon carbide powder in three different sizes. These results show that increased powder density is achievable with bimodal powder blends but is reduced in trimodal blends, and it was found that a 13% increase in the powder tap density was achieved using a bimodal blend of powder. The powder size distribution of the bimodal blend was measured at various stages during binder jet additive manufacturing and, no measurable powder separation occurred even after eight prints. Overall, this study shows limited advantage to trimodal powder blends but good promise for trimodal blends for increasing printed density while maintaining reusability in the binder jet process.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Probability Density Function for the spatial and intensity distribution of neutron-induced defects in Silicon

The ability to model semiconductor device degradation under neutron irradiation depends upon having a robust modeling capability for the neutron-induced collision cascades as well as a means to analytically fit the resulting probability distributions of defect production and ionizing energy deposition for purposes of extrapolation to low-probability, high-consequence scenarios. In this paper, the widely-utilized binary collision approximation codes MARLOWE and SRIM are deployed in conjunction with a critical examination of their parameterizations as benchmarked against higher-fidelity molecular dynamics simulations. A simple 3-parameter form described by the Generalized Logistic Distribution is shown to be a good fit to Frenkel pair and ionization intensity distributions in bulk silicon. The BCA codes are then applied to simulate cascades in 5 nm layers of a representative gate-all-around nanosheet transistor, where joint probability distributions of threshold levels of damage to multiple layers are evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

FY25 Cellular Silicone Foam Friction Testing Summary Report

This effort was a collaboration between LANL groups MPA-CINT, E-13, and V-14 to characterize various properties of foam materials for programmatic work. Specifically, MPA-CINT staff members’ contribution to this effort was to perform friction testing of cellular silicone foams of two different porosities with respect to two engineering materials with predefined surface roughnesses. The selected foams (henceforth serving as the sled material interface exposed to motion) had porosities of 67% and 70% with respect to fabricated values. The other materials used in the friction testing measurement couple (static track material) were 304 Stainless Steel (304 SS) and Very High-Temperature Glass-Mica Ceramic, known as Macor®.

36 MATERIALS SCIENCE↗