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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A sustainable cobalt separation with validation by techno-economic analysis and life-cycle assessment

Sustainable, cost-effective cobalt/nickel separations chemistry contributes to the realization of economically competitive lithium-ion battery recycling, as well as primary mining of cobalt and nickel. Such improvements can address supply chain challenges for cobalt, a critical element. Herein, we disclose a simple method for separating Co/Ni by second coordination-sphere molecular recognition. Selective cobalt precipitation is achieved using carbonate ions in an ammonia solution due to the outer-sphere, hydrogen bonding interactions between [Co(NH 3 ) 6 ] 3+ and CO 3 2− , evaluated with density functional theory calculations. We demonstrate this method on mixtures of Co/Ni chlorides comprising a 10-fold excess of Ni and provide comparisons with ore-processing systems. High purities (99.4(3)% Co; 98.2(4)% Ni) and recoveries (77(8)% Co; ∼100% Ni) were observed for both Co- and Ni-enriched products using optimized conditions. In conclusion, this method is potentially economically competitive based on initial techno-economic analysis (TEA) and life-cycle assessment (LCA) that also illustrate advantages in terms of sustainability.

cobalt↗
DOE OSTI2025

Towards robust surrogate models: Benchmarking machine learning approaches to expediting phase field simulations of brittle fracture

Data-driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning techniques have the potential to provide a much needed speedup that would enable progress in areas such as multi-scale modeling and uncertainty quantification. Currently, phase field modeling (PFM) of fracture is one such approach that offers a convenient variational formulation to model crack nucleation, branching and propagation. To date, machine learning techniques have shown promise in approximating PFM simulations. While standard fracture benchmarks represent realistic scenarios frequently observed in practice, they typically do not provide sufficiently challenging tests for data-driven methods. Here, to address this gap, we introduce a challenging dataset based on PFM simulations designed to benchmark and advance ML methods for fracture modeling. This dataset includes three energy decomposition methods, two boundary conditions, and 1000 random initial crack configurations for a total of 6000 simulations. Each sample contains 100 time steps capturing the temporal evolution of the crack field. Alongside this dataset, we also implement and evaluate Physics Informed Neural Networks (PINN), Fourier Neural Operators (FNO), and UNet models as baselines, and explore the impact of ensembling strategies on prediction accuracy. With this combination of our dataset and baseline models drawn from the literature we aim to provide a standardized and challenging benchmark for evaluating machine learning approaches to solid mechanics. Our results highlight both the promise and limitations of popular current models, and demonstrate the utility of this dataset as a testbed for advancing machine learning in fracture mechanics research.

Benchmark dataset↗
DOE OSTI2025

Universal Nuclear Accident Dosimeter

The Lawrence Livermore National Laboratory (LLNL) Universal Nuclear Accident Dosimetry (UNAD) project is a four-year initiative aimed at advancing nuclear accident dosimetry methods. This article presents an overview of the research, key findings, and the progress made throughout the project. The primary goals included a background into the history of nuclear accident dosimetry, consolidating current dosimetry techniques within the NNSA/DOE complex, fostering collaboration among subject matter experts, and exploring novel technologies for potential implementation. The technical focus centered on investigating new and novel technologies, instrumentation methods, and analysis methods to develop recommendations for a potential nuclear accident dosimeter (NAD) to be universally deployed through the DOE complex. A multilaboratory and multinational Usergroup was established, conducting periodic meetings to facilitate knowledge exchange. The UNAD team has participated in two international nuclear accident dosimetry intercomparison exercises and one characterization exercise, where the existing LLNL NAD and a prototype alanine electron paramagnetic dosimeter NAD were deployed. Ongoing improvements are being made to the prototype NAD based on results from the exercises, laboratory studies, and collaboration with other laboratories. A machine learning algorithm to optimize the geometry and conversion factors of the current LLNL NAD is being implemented, and the resulting design will be tested in the next exercise. In conclusion, key lessons learned and future directions for the project are discussed.

Electron paramagnetic resonance spectroscopy↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗
DOE OSTI2026

Mechanism of Catechol Oxidation by the Coupled Bicupric Active Site of Tyrosinase: Completion of the Oxygenase/Oxidase Reaction Cycle

Tyrosinase contains a coupled binuclear copper (CBC) active site, which in its bicuprous form (deoxy-Ty) binds O 2 to form a side-on peroxide [Cu(II) 2 O 2 ] 2+ intermediate (oxy-Ty) that performs the regioselective monooxygenation of monophenols to catechols and their subsequent 2e − oxidation to quinones. Previously, we used spectroscopic, kinetic, and computational methods to elucidate the mechanism of the initial steps in the monooxygenation reaction. Herein, we investigated the final step in catecholate formation and provide experimental and computational results elucidating the catechol oxidation reaction, formally a proton-coupled 2e − process. We employed single-turnover stoppedflow absorption to observe the elusive catecholate-Cu(II) 2 OH intermediate via the anaerobic reaction of resting Cu(II) 2 OH Ty (met-Ty) with the catecholate substrate. This intermediate was cryo-trapped and characterized by electron paramagnetic resonance and X-ray absorption spectroscopies. These experimental results were correlated to quantum mechanics/molecular mechanics (QM/MM) and QM calculations to describe the complete catalytic cycle of tyrosinase, revealing that the 2e − oxidation of catechol to quinone involves two steps: (i) coupled 1H + /1e − transfer from the bound monoanionic catecholate to the bridged hydroxide of the met-Ty active site, followed by (ii) the second 1e − transfer. The latter is calculated to be the rate-limiting step in catechol oxidation, confirmed by experimental solvent kinetic isotope effect studies. Our computational data suggest that quinone release from the protein provides the necessary driving force for this reaction. These results establish a detailed description of this oxidase cycle of the tyrosinase mechanism and more broadly provide molecular-level insights into the diverse reactivity of CBC sites in biology.

QM/MM modeling↗
DOE OSTI2025

Radiative processes on a quantum computer

Radiative processes, where a photon/neutrino is emitted as a result of a collision or decay of a particle, play a central role in atomic, nuclear, and particle physics. Their rate is determined by certain off-diagonal matrix elements between different initial and final states. We propose a method to compute them using quantum computers. It relies on a single extra qubit that, in a certain sense, represents the photon/neutrino. The generic formula relating this matrix element to the amplitude and frequency of oscillations of the extra qubit is derived for the near-resonance case. Furthermore, we demonstrate the feasibility of the method by using it in actual quantum computations and simulations of simple systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Development of a robust damage analysis scheme at the National Ignition Facility

The onset of laser-induced damage in optical materials is a limiting factor in the design and operation of most high-energy laser systems. As such, significant effort has been dedicated to developing laser damage testing protocols and procedures to inform laser system design and operating limits. These tests typically rely on multiple laser exposures for statistical validation. Historically, small beam single fluence (N / 1) or ramped fluence (R / 1) tests have been used to quantify the “laser-induced damage threshold” of a material. However, due to various distributions in damage precursor populations, the laser fluence at which damage occurs for a given sample varies with beam size and is therefore better described as the onset of observed damage for that testing geometry. In conclusion, we document the development of irradiation, measurement, and analysis methods for damage testing resulting in damage initiation density as a function of incident fluence or ρ(ϕ) which is suitable for both small and large beam area testing and more conducive to extrapolating from one to the other.

Beam diameter↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells with Location ID's ER-DOW (alias DO1West), ER-DOE (alias DO2East), ER-MBA1 (alias M1Bend1), ER-MBA2 (alias M1Bend2), ER-UPW (alias UP1West), ER-UPM (alias UP2), ER-UPE (alias UP3East). Another dataset contains the data from wells with Location ID's ER-CPA1 to ER-CPA6. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 8 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 across Meander C at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells ER-CPA1 to ER-CPA6. Another dataset contains the data from wells at nearby Locations. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 7 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Detailed Method for the Purification of Rhamnogalacturonan-I (RG-I) in Arabidopsis thaliana

The plant cell wall is a dynamic and complex extracellular matrix that not only provides structural integrity and determines cell shape but also mediates intercellular communication. Among its major components, pectins play essential roles in cell adhesion, wall porosity, hydration, and flexibility. Rhamnogalacturonan-I (RG-I), a structurally diverse pectic polysaccharide, remains one of the least understood components of the plant cell wall. Its backbone is substituted with arabinan, galactan, and arabinogalactan side chains that vary in length, branching, and composition across tissues, species, and developmental stages. In addition, RG-I can undergo modifications such as backbone acetylation, further contributing to its structural complexity and functional diversity. To advance understanding of RG-I, we present a detailed method for isolating RG-I from the model plant Arabidopsis thaliana . Leveraging Arabidopsis as a model system provides major advantages owing to its well-characterized genome and powerful molecular toolkit, enabling deeper investigation into the roles of RG-I in plant development and responses to environmental stress. Our method consists of two major steps: an initial chemical extraction using oxalate, followed by endo-polygalacturonase (EPG) digestion to fragment the pectic domains. An advantage of this approach is that it produces a dry material that can be stored at room temperature without special handling and does not introduce chemicals that may interfere with downstream analyses. The purified RG-I can be used for detailed compositional and structural analyses, as well as for functional studies of enzymes involved in pectin biosynthesis, modification, and degradation. Although this protocol was developed for isolating RG-I from Arabidopsis rosette leaves, it is also applicable to other Arabidopsis organs and other plant species.

25 ENERGY STORAGE↗
DOE OSTI2025

Development of a Miniature Small Punch Creep Test for Post Surveillance Test Specimens

Summary: This poster outlines a new small punch creep test (SPCT) for examining the mechanical properties of post surveillance test specimens. A surveillance test article was previously designed to study the effects of Molten-Salt conditions on the structural materials in the reactor. To better understand the post-test mechanical properties of the specimen, a miniature SPCT is proposed. The principle, testing standards and challenges of the method is introduced in the poster. An initial design of the testing apparatus is shown, and an experiment plan is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2024

First-Principles Simulation of Beam-Induced Processes Underlying Atomic Manipulation in Electron Microscopes

The development of experimental methods and apparatuses capable of promoting atomically precise material manipulations holds great promise for realizing the ultimate limit of feature miniaturization in materials and devices. The ability to modify materials atom by atom is anticipated to usher in new technologies in areas as diverse as separation science, medicine, and quantum information science. Historically, scanning probe-based techniques have been the most prominent approaches in this space. However, these methods are best suited for the manipulation of surface-exposed regions of materials, as the strong perturbations required for bond scission are delivered most effectively to atoms in the near-proximity to the scanning probe. In contrast, convergent electron beams with energies tuned slightly below the threshold for inducing irreversible knock-on damage have recently been employed (within scanning transmission electron microscopy) to promote atomic-scale bond rearrangements in various beam-stable solids. Currently, however, the efficiency and selectivity of beam-induced atomic manipulation processes with focused electron beams are such that long irradiation times are required to induce a desired atomic rearrangement. With a better understanding of the underlying physics dictating the outcome of a given irradiation event, methods can be devised to improve the efficiency of these techniques so that their promise can be fully realized through widespread adoption.To this end, this Account details our recent efforts to develop and apply tractable first-principles simulation approaches for studying the response of materials to electric beam-like external electric potentials applied in real space. We briefly review the concepts and capabilities in the area of atomically precise materials manipulation and review the early demonstrations of accomplishments in this area, focusing on studies using scanned convergent electron beam probes in particular. We expound upon the depth of the challenge and identify critical shortcomings of theoretical methods that have previously been employed in the simulation of beam-induced processes. We then describe the computational methods that we have generalized from the concepts and tools most commonly applied to the study of molecular photochemistry and how our adaptations of these methods can be employed to capture the relevant dynamical phenomena for beam-induced processes ranging from the initial electron scattering to the ensuing multistate reactions. Here, we contextualize these methods within the current state of the art in this area, which has historically focused primarily on the simulation of inelastic image formation in the electron microscope for the purpose of interpreting the results of quantitative electron microscopy experiments. We demonstrate that the spatial distribution of state-specific excitation rates due to the presence of an external (probe) electric charge is inhomogeneous, such that irradiation at particular locations in materials can favor specific electronic transitions (and disallow others). In addition to the potential for excited-state reaction pathways to be accessed through the initial inelastic scattering of the tightly focused electron beam from the targeted atoms, we also identify favorable conditions for the electronically nonadiabatic evolution of the highly vibrationally excited system to open complex multistate reaction pathways. Implications of the early results for understanding the mechanisms and potential routes to improved efficiency and selectivity in beam-induced reactions are discussed. We conclude with a summary of the current state of theory and modeling capabilities in this area and provide our perspective on future directions for theoretical and experimental developments that we view as crucial to advancing the use of convergent electron beams in mode-specific, atomically precise platforms for direct-write materials modifications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tuning Shinkarev’s Bicycle: Separating the Parallel Cycles of Photosystem II Using Empirical Wavelet Transform

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle.

Ferrari, Nicholas [Louisiana State Univ., Baton Ro↗
DOE OSTI2024

Investigation of thermal damage in explosive bridgewire detonators via discrete element method simulations

Exploding bridgewire (EBW) detonators are used to rapidly and reliably initiate energetic reactions by exploding a bridgewire via Joule heating. While the mechanisms of EBW detonators have been studied extensively in nominal conditions, comparatively few studies have addressed thermally damaged detonator operability. We present a mesoscale simulation study of thermal damage in a representative EBW detonator, using discrete element method (DEM) simulations that explicitly account for individual particles in the pressed explosive powder. We use a simplified model of melting, where solid spherical particles undergo uniform shrinking, and fluid dynamics are ignored. The subsequent settling of particles results in the formation of a gap between the solid powder and the bridgewire, which we study under different conditions. In particular, particle cohesion has a significant effect on gap formation and settling behavior, where sufficiently high cohesion leads to coalescence of particles into a free-standing pellet. This behavior is qualitatively compared to experimental visualization data, and simulations are shown to capture several key changes in pellet shape. We derive a minimum and maximum limit on gap formation during melting using simple geometric arguments. In the absence of cohesion, results agree with the maximum gap size. With increasing cohesion, the gap size decreases, eventually saturating at the minimum limit. In conclusion, we present results for different combinations of interparticle cohesion and detonator orientations with respect to gravity, demonstrating the complex behavior of these systems and the potential for DEM simulations to capture a range of scenarios.

cohesive powders↗
DOE OSTI2026

Parallel-in-Time Solution of Allen-Cahn Equations by Integrating Operator Learning into the Parareal Method

While recent advances in deep learning have shown promising efficiency gains in solving time-dependent partial differential equations (PDEs), matching the accuracy of conventional numerical solvers still remains a challenge. One strategy to improve the accuracy of deep learning-based solutions for time-dependent PDEs is to use the learned model as the coarse propagator in the Parareal method and a traditional numerical method as the fine solver. However, successful integration of deep learning into the Parareal method requires consistency between the coarse and fine solvers, particularly for PDEs exhibiting rapid changes such as sharp transitions. Here, to ensure this consistency, we propose using convolutional neural networks (CNNs) to learn the fully discrete time-stepping operator defined by the same numerical scheme employed as the fine solver. We demonstrate the effectiveness of the proposed method in solving the classical and mass-conservative Allen–Cahn (AC) equations. Through iterative updates in the Parareal algorithm, our approach achieves a significant computational speedup compared to traditional fine solvers while converging to high-accuracy solutions. Our results highlight that the proposed hybrid Parareal algorithm effectively accelerates simulations, particularly when implemented on multiple GPUs, and converges to the desired accuracy in only a few iterations. Another advantage of our method is that the CNN model is trained on trajectory-based data generated from random initial conditions, such that the trained model can be used to solve the AC equations with various initial conditions without retraining. This work demonstrates the potential of integrating neural network methods into parallel-in-time frameworks for efficient and accurate simulations of time-dependent PDEs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Initial Alloy 709 constitutive models for use with the ASME design by inelastic analysis and EPP+SMT design methods

This report details a preliminary inelastic constitutive model describing the behavior of Alloy 709. This model will serve two purposes: (1) integration into Nonmandatory Appendix HBB-Z of the ASME Boiler & Pressure Vessel Code Section III, Division 5 and (2) extrapolating cyclic test data to difficult to measure conditions for formulating improved creep-fatigue design methods. For both applications, the model must accurately capture the material behavior across a wide range of temperatures and a variety of test conditions, both monotonic and cyclic. For this purpose we adopt a universal model form under consideration to standardize the description of high temperature constitutive models in the ASME Code. This report briefly restates that model form and how we calibrate the model against the test data, summarizes the test database, and validates the final, trained model by comparison to the experimental tests.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Destructive Analysis of TRISO Particles: Crush/Burn/Leach Followed by Davies-Gray Titration and IDMS

The accurate accounting of nuclear materials is a cornerstone of international nuclear safeguards. One emerging challenge in this domain is the fabrication of TRIstructural ISOtropic (TRISO) particle fuels. Although these innovative fuel forms are critical for advanced reactor applications, their robust refractory ceramics and coating compositions present significant obstacles to destructive analysis (DA) methods. Ensuring full and quantitative recovery from these particles is essential for accurate mass accountancy. The current study was initiated to address these challenges, first by validating a previously established destructive method developed by Oak Ridge National Laboratory (ORNL) for the quantitative recovery of uranium from TRISO particles and then following that process with uranium content determination through isotope dilution mass spectrometry (IDMS) and Davies-Gray titration. This study expands on the scope of a digestive method that was developed under the Advanced Gas Reactor Fuel Development and Qualification program and is currently implemented in both the Coated Particle Fuel Development Laboratory and Irradiated Fuels Examination Laboratory at ORNL. The success of the previous Advanced Gas Reactor work relied on developing a DA method to evaluate the fabrication process and reactor experiments. The methodology described in this report was designed to rigorously investigate the efficacy of the crush/burn/leach sample preparation of TRISO particles; it aims to quantify uranium recovery while also assessing the effects of TRISO constituents (e.g., silicon and zirconium) on analytical precision and accuracy. By comparing the results from the titration method and IDMS, we sought to determine whether existing analytical procedures accepted by the International Atomic Energy Agency (IAEA) could be effectively translated to TRISO fuel forms. The team employed an approach that involved processing replicate TRISO samples, optimizing the milling (i.e., crushing) step and performing serial leaches. The elemental composition of the analytical samples was examined to prepare for interference studies in the second year of this project. The integration of gamma spectrometry to verify residual uranium activity further strengthened the validation. Statistical methods were applied to the collected data to evaluate the uncertainties arising from sampling, sample preparation and uranium quantification. These uncertainties were then compared to the IAEA’s international target values (ITVs). Additional data collected in upcoming project work will strengthen the uncertainty estimates. Ultimately, it is hoped that this project will contribute materially to the body of work related to characterization of TRISO based fuels for the purpose of material accountancy and its applications to international safeguards.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Nuclear Structural Component Relevant Properties of Nickel-Based Alloys Produced via Additive Manufacturing

Idaho National Laboratory initiated examination of nickel-based alloys manufactured via three different additive manufacturing methods for potential applications in nuclear, high temperature structural components. The three methods analyzed included laser powder bed fusion, blown powder laser directed energy deposition, and wire-fed gas metal arc directed energy deposition. With the rapid push towards additive manufacturing, codes do not exist that definitively define what is or is not tolerable for each process and application, such as with conventional, wrought products. This report contains the initial work to understand possible manufacturing methods for high temperature alloys, and specifically, void formation, microstructure evolution, corrosion, and mechanical properties. To generate mechanical test data, specimens were tested irrespective of voids and microstructures were analyzed to better understand how to negate/improve these issues. The preliminary results showed major decreases in mechanical performance for material tested. Test specimens will continue to be produced to further improve each additive manufacturing processes, quantify void acceptance, and better understand the most suitable high temperature alloys receptive to additive manufacturing and high temperature nuclear applications.

36 MATERIALS SCIENCE↗