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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Steam oxidation and microstructural evolution of rare earth silicate environmental barrier coatings

A primary failure mode for environmental barrier coatings (EBCs) on SiC ceramic matrix composites (CMCs) is the oxidation of the intermediate Si-bond coating, where the formation of SiO 2 at the bond coating–EBC interface results in debonding and spallation. This work compares the microstructure evolution and steam oxidation kinetics of the Si-bond coating beneath yttrium/ytterbium disilicate ((Y/Yb)DS) and ytterbium disilicate/monosilicate (YbDS/YbMS) EBCs to better understand the impact of EBC composition on oxidation kinetics. After 500 1-h cycles at 1350°C, (Y/Yb)DS displayed a decreasing concentration of the monosilicate minor phase and increasing concentration of porosity as furnace cycling time increased, whereas the YbDS/YbMS EBC displayed negligible microstructural evolution. For both EBC systems, thermally grown oxide growth rates in steam were found to increase by approximately an order magnitude compared to dry air oxidation. The (Y/Yb)DS EBC displayed a reduced steam oxidation rate compared to YbDS/YbMS.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phase stability and tensorial thermal expansion properties of single to high-entropy rare-earth disilicates

Temperature limitations in nickel-base superalloys have resulted in the emergence of SiC-based ceramic matrix composites as a viable replacement for gas turbine components in aviation applications. Higher operating temperatures allow for reduced fuel consumption but present a materials design challenge related to environmental degradation. Rare-earth disilicates (RE 2 Si 2 O 7 ) have been identified as coatings that can function as environmental barriers and minimize hot component degradation. In this work, single- and multiple-component rare-earth disilicate powders were synthesized via a sol-gel method with compositions selected to exist in the monoclinic C 2/m phase (β phase). Phase stability in multiple cation compositions was shown to follow a rule of mixtures and the C 2/m phase could be realized for compositions that contained up to 25% dysprosium, which typically only exists in a triclinic, P $\bar1$, phase. All compositions exhibited phase stability from room temperature to 1200°C as assessed by X-ray diffraction. The thermal expansion tensors for each composition were determined from high-temperature synchrotron X-ray diffraction and accompanying Rietveld refinements. It was observed that ytterbium-containing compositions had larger changes in the α 31 shear component with increasing temperature that led to a rotation of the principal axes. Principal axes rotation of up to 47° were observed for ytterbium disilicate. The results suggest that microstructure design and crystallographic texture may be essential future avenues of investigation to ensure thermo-mechanical robustness of rare-earth disilicate environmental barrier coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2024

Understanding EBC Lifetimes and Performance for Industrial Gas Turbines

Hydrogen or hydrogen blend fuels are expected to replace natural gas in land-based industrial gas turbines (IGTs) to support a greener power economy. Silicon carbide (SiC) base ceramic matrix composites (CMCs) are considered for replacement of Ni-based superalloys to facilitate future efficiency improvements. SiC CMCs require environmental barrier coatings (EBCs) to mitigate volatilization from high-temperature steam, thus making the EBC lifetime critical information for identifying CMC component lifetimes. The goal of this project is to determine the maximum bond coating temperature underneath the EBC for achieving an IGT component lifetime goal of 25,000 h, which is far greater than current CMC component lifetime requirements for aero-turbine applications. To provide data for the lifetime model, laboratory testing used plasma-sprayed rare-earth silicate EBCs on monolithic SiC substrates with an intermediate Si bond coating. Specimens exposed to 1-h thermal cycles in flowing air-steam environments and reaction kinetics were assessed from 700°-1350°C by measuring the thickness of the thermally grown silica scales. The silica growth and phase transformation appear critical in predicting EBC lifetime and several strategies have been explored to reduce the oxide growth rate and improve EBC durability at elevated temperatures. Advanced characterization using Raman spectroscopy has helped clarify this system.

Ridley, Mackenzie↗
DOE OSTI2025

Characterization of Heat Transfer in a Trapped-Vortex Combustor Designed for High-Temperature Material Testing

Next generation gas turbines will reduce carbon emissions by improving their cycle efficiencies and implementing hydrogen as a low-carbon fuel. The combined-cycle efficiency can be improved by increasing the combustor outlet temperature and decreasing the cooling air required for hot-section parts. Ultra-high temperature ceramic matrix composites (CMC) can survive increasingly extreme environments due to their strong mechanical properties at expected conditions. The introduction of CMCs in high-hydrogen flame environments requires testing at realistic conditions that mimic the thermochemical and fluid mechanic states in gas-turbine combustors. In this work, we describe a new experiment that has been designed to test high-temperature materials in a combustor-relevant environment. Its trapped-vortex combustor chamber design allows for high levels of fuel flexibility and wide flame stability limits. Testing of monolithic silicon carbide (SiC) samples in this environment was done to characterize the heat transfer to material samples over a wide range of operating conditions, including variations in fuel composition and thermal power. Heat flux measurements were verified in non-reacting and reacting environments after which they were benchmarked with previous literature to verify the operation of the facility with heated air. Testing in combustor-relevant conditions shows high levels of heat flux to the material samples in the combustor, particularly downstream of the anchored flame.

Richins, Porter [Pennsylvania State University , ,↗
DOE OSTI2022

Compressive strength of the plastic-bonded explosive surrogate idoxuridine under quasistatic and dynamic compression

Inert simulant materials, or “mocks”, are often used as surrogates for plastic-bonded explosives (PBX) in non-detonative tests in order to mitigate hazards. Mocks should reproduce as many non-detonative properties of the explosive as possible, including structural behavior in a variety of thermal and mechanical environments. Recently, the molecular crystal idoxuridine (IDOX) has been identified as an ideal mock for the main component in the explosive polymer-matrix composite PBX 9501, and has performed favorably under quasistatic loading conditions. Here, in order to assess robustness over a range of mechanical environments, plastic-bonded IDOX was compression tested from 0.001/s to 2000/s strain rates and compared to PBX 9501 historical data. Plastic-bonded IDOX showed good agreement to PBX 9501 across these strain rates, justifying continued development and production as a mock.

Burch, Alexandra C.↗
DOE OSTI2022

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗
DOE OSTI2020

Additive Manufactured Metallic 3D Ox-Ox CMC Integrated Structures for 65% Combined Cycle Efficient Gas Turbine Components

To support the FOA objectives for the Area of interest “Advanced Combustion Turbines for Combined Cycle Applications”, Phase I initially targeted the integration of Metallic Additive Manufacturing (AM) and 3D Oxide-Oxide Ceramic Matrix Composites (3D Ox-Ox CMC) based design for an Advanced Vane design in support of 65% efficient gas turbines. Application of an AM-CMC-TBC vane was expected to significantly reduce cooling air consumption and result in emissions and/or performance improvements beyond the current SOTA metallic vane technology. The primary deliverable was a design concept ready for fabrication and test in a follow-on (Phase II) project.

03 NATURAL GAS↗
DOE OSTI2021

HFIR SiC Bowing Test Ready to Insert

This report describes the successful assembly of a High Flux Isotope Reactor (HFIR) irradiation experiment designed to assess radiation-induced lateral bowing of silicon carbide fiber–reinforced, silicon carbide matrix composite (SiC/SiC) components under a radial fast neutron flux gradient. Excessive bowing of a SiC/SiC channel box in a boiling water reactor could potentially interfere with control blade movements. Similar concerns exist for SiC/SiC fuel cladding in light water reactors. The experiment described herein will provide experimental validation of the structural response of a miniature SiC/SiC channel box and tube specimens with pressurized water reactor diameters during irradiation. The significant radial fast neutron flux gradients that exist in the permanent reflector of HFIR were characterized using detailed three-dimensional neutronic calculations. The three-dimensional displacement damage dose rate profile and the resulting volumetric swelling in SiC were used as inputs to structural analyses that predicted the deformation and stresses in the channel box specimen. The specimens were thoroughly characterized prior to irradiation using traditional dimensional inspection and surface profilometry so that these measurements can later be compared with similar measurements that will be made post-irradiation to determine radiation-induced deformations. Furthermore, fine engraving markers were inscribed along all outer surfaces of the specimen and mapped using a digital microscope and a three-dimensional stage. This technique allowed for accurate measurements of the marker spacings, which can be compared with similar measurements that will be made post-irradiation to provide local radiation-induced strain mapping. The experiment was successfully assembled and is scheduled for insertion during HFIR cycle 492, which is currently scheduled to run from May 25, 2021 to June 18, 2021.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Advanced Multi-Tube Mixer Combustion for 65% Efficiency (Final Report)

This project targeted advanced low NOx combustion for advanced gas turbines capable of 65%, or greater, efficiency in combined cycle application. This technology advancement has further potential to benefit gas turbines used in coal based IGCC applications with pre-combustion carbon capture and hydrogen as the resulting fuel. The program developed and synthesized the most advanced combustion system capable of achieving low NOX emissions up to turbine inlet temperatures of 3100F while also supporting the load-following needs of a modern grid. The combustion system contributes to the overall gas turbine efficiency goal by setting the maximum cycle temperature achievable for a given NOX level and by minimizing the through-combustor air flow pressure drop. Focus areas for this project targeted maximizing the turbine inlet temperature entitlement, as constrained by emissions considerations. The design also minimized parasitic air flow pressure drop by using advanced cooling techniques and performance materials selections and by minimizing hot surface area. These two technology objectives (maximum, emissions-compliant cycle temperature and minimum air flow pressure drop) were integrated into a prototype design. The primarily analytical project sought to identify the most promising technologies to meet these objectives. Additional critical “jugular” data were obtained from multi-tube mixer tests to realize the potential of leveraging “micro flames” for minimizing overall hot surface area. This data was used, in conjunction with an understanding of advanced material and cooling design technologies, to analytically develop multiple design concepts. Phase I focused on in-depth engineering analysis and design, with minimal supporting laboratory testing to enable a selection of the top three combustion architectures for achieving these overall objectives. Phase II of the program developed the selected design through a combination of sub-scale testing and analytical efforts. Early tests included a cold-flow cascade to establish aerodynamic performance characteristics and a sub-scale fired test at GE Global Research in Niskayuna, NY, to establish cooling and heat transfer characteristics in conjunction with combustion performance. The data from these tests validated the analytical models to ultimately design a full-scale, test article to evaluate at prototypical pressure and temperature conditions at GE Gas Power’s Gas Turbine Technology Laboratory in Greenville, SC. GE Gas Power also developed, tested, and recommended a suitable seal design to be applied to the unique features of the combustor. To assess the technology challenges from prospective future production of the combustor from a ceramic matrix composite material, screening tests of Environmental Barrier Coatings were completed.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

High Level Gap Analysis for Accident Tolerant and Advanced Fuels for Storage and Transportation

This initial gap analysis considers proposed accident tolerant fuel (ATF) options currently being irradiated in commercial reactors, since these are most likely for future batch implementation. Also, advanced fuel (AF) options that may be likely for use in advanced reactors are considered. The cladding technologies considered were chromium-coated zirconium-based alloys, FeCrAl, and both monolithic and matrix composite Silicide carbide (SiC). The fuel technologies considered were chromium-doped uranium dioxide fuel, uranium alloys, uranium nitride, and uranium silicide. Numerous national labs, industry, and countries are performing significant testing and modeling on these proposed technologies to establish performance, but at this time none of the prototypes being irradiated have achieved end-of-life (EOL) burnup. There are some testing results after one burnup cycle to verify in-reactor performance, but little data beyond that. As the ATF prototypes acquire more burnup, data will be produced that is relevant to storage and transportation. The DOE:NE Spent Fuel and Waste Science and Technology (SWFST) Storage and Transportation (ST) Control Account will evaluate the performance data as it becomes available for application to the identified gaps for ST.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Analysis Report for Determination of pH Correction Factors for Brines under AP-157 Rev.1

This Analysis Report (AR) documents the determination of pH correction factors for the observed pH readings. The correction factor converts the observed pH reading recorded from the brines used in geochemical studies in support of the Waste Isolation Pilot Plant (WIPP) to a corrected pH value. The data analysis in this AR falls under AP-157 Rev. 1 Analysis Plan for Determination of pH Correction Factors in Brines (Kirkes et al, 2021). Measurement of pH in some solutions can be challenging due to numerous factors such as high ionic strength, elevated or lowered temperature, complex matrix composition, etc. (Knauss et al., 1990; and Rai et al., 1995). The measured pH can be corrected by applying the correction factor, empirically obtained from a specific test solution.

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

Modeling the Effects of Microwave Heating on Densification in Chemical Vapor Infiltration

Microwave heating has great potential to accelerate the synthesis of ceramic matrix composites (CMCs) by a process called Chemical Vapor Infiltration (CVI). In CVI, reactive gases ingress a porous preform and undergo chemical transformation to deposit solid ceramic phase within the pores at high temperature thus, densifying the preform. However, the competing effects of chemical kinetics and gas transport are known to result in non-uniform densification as the outer surfaces of the preform experience faster depositions compared to the core. Achieving spatial temperature control plays a key role improving the densification quality. Microwave heating can potentially create temperature inversion such that the core of the preform is hotter than the outer surface and subsequently, lead to improved densification while keeping the manufacturing times and costs low. In the present work, a computational modeling strategy has been developed that accounts for the key physical phenomena responsible for densification of porous preforms using microwave heating. Specifically, a chemical kinetics model has been formulated for Silicon Carbide (SiC) deposition from MTS/H2 precursor. The model is implemented in a pore-resolved reactive transport solver, Quilt. The CVI simulations are performed for several conditions. Initially, parameterized temperature control is imposed to identify optimum conditions for good densification quality at a fraction of processing time. Further, simulations of microwave heating of porous SiC preforms are performed using OpenFOAM. A strategy to achieve and enhance temperature inversion is identified. The resulting temperature profiles are used in the pore-resolved densification simulations to analyze the densification behavior. It is observed that the temperature inversion achieved by microwave heating leads to significant improvements in densification quality and at the same time, keeps the manufacturing time low.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The material challenges of the next generation of concentrated solar power

This is an introductory seminar about the cleantech-to-market pathway with a focus on material innovation in Concentrated Solar Power. This seminar will first lay out the business model of cleantech companies to identify the players in technical innovation. With a summary of the desires of the major player, this seminar will dive into the possibility, potential, and challenges of next-generation Concentrated Solar Power to answer these desires, followed by a detailed discussion on the material challenges. The scope of our project “Scalable, Infiltration-Free Ceramic Matrix Composite for the molten salt receiver” will be presented as one potential way to solve these challenges. In the end, this seminar will present some job opportunities to inspire the audience to participate in cleantech innovation.

42 ENGINEERING↗
DOE OSTI2023

Shear Assisted Processing and Extrusion (ShAPE) of Plastics: Recycling and Remolding

Polyethylene (PE) and polypropylene (PP) are often disposed as mixed plastic wastes. The challenges in recycling and upcycling these mixed polyolefin wastes lie in the difficulty in separating individual constituents in a cost-effective and scalable manner. Direct recycling the mixed PE and PP wastes in conventional melt-phase extruders typically result in a product with poor properties and low added value, because of immiscibility, phase separation, and lack of crystallinity. Friction extrusion (FE), a solid phase processing technique that has successfully extruded metal matrix composites with desired end products, has never been utilized to address the issue of recycling mixed plastic wastes. In this study, FE was performed on single-stream low-density polyethylene (LDPE), single-stream PP and mixed-stream LDPE+PP. Consolidated filaments of 2.5 mm diameter were extruded from different precursors. The thermal, infrared, and microscopic properties of extruded filaments were measured to evaluate the effects of FE process on the structure of recycled polymers. Meanwhile, the energy efficiency of FE was estimated based on extrusion rates and compared with conventional melt extrusion processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $6B annually (at $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year),and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE)missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Surface Tagging of Al 6061-T6 using Photoluminescent Oxides

The goal of tagging nuclear fuels (or related materials, such as fuel cladding) is to provide a persistent marker, traceable to the fuel manufacturer, that can be detected after some length of time, likely after the fuel has been lost, rerouted, or partially destroyed. Ideally, the tag is complicated enough to encode data pertaining to the provenance (manufacturer, date or time, constituents, etc.) and robust enough to survive in-pile exposure and/or further destruction. The taggant should not change the behavior or performance of the fuel in any meaningful way. Photoluminescent tagging was an attractive solution to many of these challenges, as it is undetectable under normal lighting conditions, visible to the naked eye under specific lighting conditions, does not require a significant quantity of material to be photoluminescent, observable with simple commercial detection tools, and is versatile and robust in application. In FY23, the team focused on embedding photoluminescent taggants onto the replicate fuel cladding surface using welding. From a welding standpoint, photoluminescent taggants, in the form of oxides, are a viable option for tagging because the taggants have high melting points, and thus likely to survive welding temperatures (i.e., remain as a secondary phase particle and maintain luminescent properties). Additionally, these taggants have the potential to act as a metal matrix composite which may increase the strength-to-weight ratio, stiffness, and ductility of the base material, all beneficial to cladding and fuel performance.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗