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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Chemically Inert Hydrocarbon-Based Slurries for Rapid Laser Sintering of Thin Proton-Conducting Ceramics

The process of rapid laser sintering of thin BaZrO 3 –BaCeO 3 -based proton-conducting electrolytes is being developed for easy fabrication of ceramic fuel cells and electrolyzers. However, cracks on the electrolytes caused by volume change due to chemical reactions between the basic ceramic constituents and the polar solvents during wet processing has been problematic. In order to address this issue, the use of chemically inert saturated-hydrocarbon-based slurries comprised of hexadecane, polybutene, and a long-chain saturated fatty acid were investigated in this work. By optimizing slurry composition and laser sintering conditions, a 20 mm long, 4 mm wide, 13.5-μm-thick and 97%-dense BaCe 0.7 Zr 0.1 Y 0.07 Sm 0.13 O 3-d membrane showing proton conductivity on the order of 10 –4 S•cm –1 at 600 °C was successfully prepared in just three seconds by laser sintering. As a result, the use of saturated-hydrocarbon-based slurries will facilitate wet processing and rapid laser sintering of proton-conducting ceramic electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiobjective Modular Biorefinery Configuration under Uncertainty

With increasing interest in using biomass as a raw material for fuel, the development of biorefineries is an active area of research. However, increasing market competition, uncertainty, and environmental concerns are a few of the challenges that need to be addressed. In this work, mathematical optimization formulations are proposed to address these challenges simultaneously. A multiobjective deterministic optimization framework is proposed to address economic and environmental objectives. A two-stage stochastic optimization framework is proposed to account for uncertainties in material flow and product yields. To model the environmental objective, an environmental risk metric is proposed. Finally, as modularization is gaining popularity in the process industry due to its ability to save capital cost because of standardization and reduce time to market, a formulation for simultaneously achieving modular process design and biorefinery configuration is proposed. Furthermore, the results demonstrate the efficacy of the proposed approach.

09 BIOMASS FUELS↗
DOE OSTI2022

Carboxylic acid ligand substituent impacts hydrosilylation activity of platinum single atom catalysts on ceria

Current industrially employed hydrosilylation catalysts rely on homogeneous platinum catalysts which are not recovered after the reaction. To eliminate this issue, our group has been working to optimize recyclability of heterogeneous platinum single atom catalysts (SACs) on ceria via 1,10-phenanthroline-5,6-dione ligands (PDO), which incorporates mono (PDO-C) and dicarboxylic acid (PDO-C2) groups in the 2- and 9-position of PDO ligand to increase metal–surface interaction. DRIFTS results confirm carboxylic acid coordination to the terminal hydroxy groups of the ceria surface. New catalyst synthesis conditions wherein PDO was combined with the metal prior to exposure to the surface allow control of Pt oxidation state on the surface. Here, the highest metal loading was observed for PDO and PDO-C, correlating with improved catalytic recyclability compared to the PDO-C2 ligand. It is proposed that the location of the carboxylic acid groups and the steric effects can explain the lower activity and metal loading for PDO-C2 ligands. Post-reaction XPS and DRIFTS spectra show the appearance of new Si and O species on the catalyst during the hydrosilylation reaction, indicating the silane reagent is depositing on the surface. The silane coverage and leaching of catalyst from the surface is the cause for the reduced catalytic activity.

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

DLIO: A DATA-CENTRIC BENCHMARK FOR DEEP LEARNING APPLICATIONS

SF-22-136 Deep learning has been shown as a successful method for various tasks, and its popularity results in numerous open-source deep learning software tools. Deep learning has been applied to a broad spectrum of scientific domains such as cosmology, particle physics, computer vision, fusion, and astrophysics. Scientists have performed a great deal of work to optimize the computational performance of deep learning frameworks. However, the same cannot be said for I/O performance. As deep learning algorithms rely on big-data volume and variety to effectively train neural networks accurately, I/O is a significant bottleneck on large-scale distributed deep learning training. DLIO, is a novel representative benchmark suite built based on the I/O profiling of the selected workloads. DLIO can be utilized to accurately emulate the I/O behavior of modern deep learning applications. Using DLIO, application developers and system software solution architects can identify potential I/O bottlenecks in their applications and guide optimizations to boost the I/O performance leading to lower training times. The storage vendor can also use DLIO as a guide for designing and optimize the storage and filesystem targeting at deep learning application.

ZHENG, HUIHUO↗
DOE OSTI2023

Measurement-induced entanglement phase transitions in variational quantum circuits

Variational quantum algorithms (VQAs), which classically optimize a parametrized quantum circuit to solve a computational task, promise to advance our understanding of quantum many-body systems and improve machine learning algorithms using near-term quantum computers. Prominent challenges associated with this family of quantum-classical hybrid algorithms are the control of quantum entanglement and quantum gradients linked to their classical optimization. Known as the barren plateau phenomenon, these quantum gradients may rapidly vanish in the presence of volume-law entanglement growth, which poses a serious obstacle to the practical utility of VQAs. Inspired by recent studies of measurement-induced entanglement transition in random circuits, we investigate the entanglement transition in variational quantum circuits endowed with intermediate projective measurements. Considering the Hamiltonian Variational Ansatz (HVA) for the XXZ model and the Hardware Efficient Ansatz (HEA), we observe a measurement-induced entanglement transition from volume-law to area-law with increasing measurement rate. Moreover, we provide evidence that the transition belongs to the same universality class of random unitary circuits. Importantly, the transition coincides with a “landscape transition” from severe to mild/no barren plateaus in the classical optimization. Our work may provide an avenue for improving the trainability of quantum circuits by incorporating intermediate measurement protocols in currently available quantum hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Revolutionizing Turbine Cooling with Micro-Architectures Enabled by Direct Metal Laser Sintering

The objective of this research effort was to explore innovative cooling architectures enabled by additive manufacturing techniques for improved turbine cooling performance. The ability to create complex internal geometries was leveraged to better distribute coolant as well as to integrate inherently unstable flow devices to enhance internal and external heat transfer. This was accomplished with a multi-faceted approach including analytical, experimental, and computational components. This final report documents progress during the total 4.25 year effort that was extended (at no additional cost) from the original 3-year cooperative agreement. Prior to starting the project, significant effort was invested in investigating innovative cooling designs from the open literature. When the project started, we quickly down-selected to 4 configurations: impingement jet fluidic oscillators (for internal leading edge cooling), reverse film cooling (for pressure surface), sweeping film cooling jets (for suction surface), and trailing edge slot cooling with microchannels. During the 2nd year, the reverse film cooling design was shown to be sub-optimal and work on that topic was halted. The three remaining technologies were integrated into a large scale nozzle guide vane and installed into a low-speed linear cascade facility for further interrogation. Initial results showed the sweeping film cooling jets (on the suction surface) to be the most promising technology compared to a baseline diffusion shaped film hole (777 design). The benefit was particularly evident at high blowing ratios (>1.5) when the 777 coolant film separated from the downstream surface. Benefits were also evident at elevated freestream turbulence levels. The leading edge cooling with unsteady jets was less effective in terms of peak or average cooling – however it was superior to round hole impingement cooling in terms of spatial uniformity. Finally, the trailing edge cooling design with micro-channels was scrapped in favor of a pinned arrangement with centerbody. During the 3rd year, the same three technologies were integrated into a transonic linear cascade for an assessment of compressibility effects. Again, the sweeping film cooling jets proved superior at high blowing ratios while the unsteady leading edge impingement and trailing edge pin-fins with centerbody designs yielded mixed results. Finally, during the 4th and final year, these 3 technologies were integrated into a direct metal laser sintered (DMLS) nozzle guide vane for testing in a high temperature, transonic annular vane cascade. The facility matches the flow temperature, Mach number, and coolant pressure ratios of an actual gas turbine. Before doing this, an additional series of tests were completed to validate a redesigned trailing edge cooling architecture. This final design included a centerbody with triangular pins between the centerbody and the vane external skin. The majority of these triangular pins are fabricated with a 30% gap to the centerbody – reducing their pressure drop considerably while still providing excellent heat transfer augmentation. This additional test campaign required an additional 3-month extension request to complete testing in the high temperature NGV test facility (Turbine Reacting Flow Rig – TuRFR). Testing of the DMLS vane in TuRFR pitted the 3 innovative cooling technologies against more traditional technologies (shaped 777 film hole, round impingement jet, and full pin arrangement in the trailing edge. The sweeping film cooling jets (on the suction surface) showed approximately 15% improvement in overall effectiveness compared to the 777 film hole while the trailing edge showed up to 20% improvement. The leading edge impingement was disappointing with a substantially lower effectiveness than traditional direct impingement. In summary, the study was successful in demonstrating that DMLS-enabled cooling technologies can yield significant gains in cooling performance.

03 NATURAL GAS↗
DOE OSTI2020

Copper Evaluation and SCALE S/U [Slides]

This presentation discusses progress that has been made so far on the RRR evaluation for n+ 63,65 Cu and on SCALE S/U work, especially optimizations for TSUNAMI-IP.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

System Integration of Rationally Designed Dilute Alloy Catalysts for Energy-Efficient Electrochemical CO 2 -To-Fuel Conversion

Energy effiecient electrochemical conversion of CO 2 to high-demand chemicals and transportation fuels using renewable solar and wind energy is a key technology needed for a high-productivity, low-carbon future. However, the development of scalable, low-cost, active, selective, and stable electrocatalysts remains a key challenge that needs to be overcome to enable high-volume conversion of CO 2 to feedstock chemicals for the chemical industry. In previous work, Lawrence Livermore National Laboratory (LLNL) has developed a rational design platform for dilute alloy transition metal electrocatalysts that promise to make electrochemical CO 2 conversion more energy efficient and selective. In this project, we worked with our industrial partners, Twelve and TotalEnergies, to improve scale up, integration, and stability of LLNL’s dilute alloy catalyst technology into an industry-relevant zero gap electrolyzer platform. Through virtual experiments and data analysis, we designed efficient and cost-effective copper-based catalysts. The catalyst was specifically designed to streamline the slowest and most energy-intensive step of the electrochemical chemical transformation of CO 2 to multi-carbon products – that is making the carbon-carbon bond by dimerization of the reaction intermediate carbon monoxide - resulting in up to 10% improvement in energy efficiency for C 2 products while simultaneously increasing the selectivity towards C 2 products. We tested two different scalable catalyst coating technologies and down-selected magnetron sputtering as the technique that provided the best control over catalyst loading, composition, and morphology. Using this technology, we successfully demonstrated integration of our dilute alloy catalysts into a 100 cm 2 electrolyzer platform with Faradaic efficiencies for ethylene production reaching 40% at a current density of 200 mA/cm 2 . We also developed the technology to integrate a well-defined nanoscale porosity by depositing alloy compositions that were compatible with dealloying, that is, selective leaching of an alloy component to generate nanoscale porosity. We observed that integration of the dealloying-derived nanoporosity improved catalyst performance and stability by leading to a more hydrophobic catalyst/anion exchange membrane interface. Unsolved problems that still need to be addressed are corrosion of the Cu catalyst -specifically if the used catalyst is exposed to air - as well as long term stability do to salt formation/deposition and flooding of the catalyst/electrolyzer flow channels, especially at higher current densities. As we only worked on optimization of catalyst composition, coating thickness, and morphology, further performance optimization will require a system level approach that includes optimization of electrolyzer design and membrane technology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deep Learning At Depth: Estimating subsurface parameters from geophysical monitoring data

Geophysical imaging techniques are a non-invasive way to image the subsurface and understand both subsurface solid (rock/soil) and fluid property distributions and their evolution in time. Inversions of the geophysical data, such as Electrical Resistance Tomography (ERT) data, are solved to estimate the subsurface property distributions, such as conductivity, and many inversion techniques smooth out sharp gradients in rock or fluid property distributions. Sharp gradients in subsurface properties tend to be present in situations with complex subsurface structures, which are common in many subsurface applications. We have successfully demonstrated that it is possible to inform, or constrain, inversions with neural networks trained on synthetic data with complex subsurface structures. Initial results suggest this process may be optimizable to yield property distributions that better represent the true property distributions than the same inversion process without the neural network constraint. Future work would optimize the neural network performance for this application and then apply the synthetic-data trained neural network to real data to understand the utility and performance of this technique for real data sets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

An ICME Modeling Framework for Metal Matrix Composites Focusing on Ultrahigh Temperature Matrix Material and Tungsten Carbide Reinforcement Particulate (Final CRADA Report)

Ultra High Temperature Metal Matrix Composites (UHT-MMCs) are of interest to the due to their potential defense and aerospace applications. These materials consist of a metal matrix reinforced with a stiff ceramic or cermet. Based on a preliminary literature survey, this project will focused on a pure titanium (Ti) matrix reinforced with tungsten carbide-cobalt (WC-Co). UHT-MMC technology is still at a nascent stage of development and requires extensive experimental work to optimize the structure and resulting material properties of a particular UHT-MMC material system. An accurate and complete high-performance computing (HPC) model of the Ti/WC-Co material system could greatly accelerate the development and deployment Ti/WC-Co materials by connecting processing parameters to material properties. This type of model could then be used in an integrated computational materials engineering approach to optimize the material structure to achieve a targeted level of performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid Laser Reactive Sintering of Garnet Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 and Li 6.1 La 3 Zr 2 Al 0.3 O 12 and Solid-State Electrolytes

All solid-state lithium-ion batteries (ASSLIBs) have gained significant interest in recent years due to their wide range of applications, including mobile devices, electric vehicles, and grid storage. Garnet-type Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolyte (SSE) continues to be a significant player in the fabrication of ASSLIBs with excellent ionic conductivity on the order of 10 -3 S•cm -1 with the integration of dopants and sintering aids to assist conductivity and structural evolution during the sintering procedure. Traditional sintering techniques, such as solid-state sintering (SSS), have been proven to yield desirable crystal structures. However, the low ionic conductivity results from inferior microstructure, and lithium loss is a significant challenge. Recently, a relatively novel sintering process called rapid laser sintering (RLS) has shown great potential for achieving fully dense solid oxide electrolytes with less lithium loss, resulting in high ionic conductivity [1] [2] [3] [4]. Here, we applied a modified RLS method using precursor powders instead of pre-synthesized LLZO powders to fabricate Al-doped LLZO (Li 6.1 La 3 Zr 2 Al 0.3 O 12 + 13 wt% Li 2 CO 3 ) and Ta-doped LLZO (Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 + 5 wt% LiOH•H 2 O) dense electrolytes. This rapid laser reactive sintering (RLRS) could potentially reduce the number of processing steps and therefore lower the manufacturing cost. We hope the rapid high-temperature sintering can densify the electrolyte and avoid the lithium loss for achieving high lithium-ion conductivity. In this work, we optimized a combination of laser parameters (speed and power), initial precursor composition, and controlled atmospheres to discover the optimal conditions for reaching the efficacious crystal structure, microstructure, and ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2023

Direct Air Capture of Carbon Dioxide Using Nickel Hydroxide Batteries in a Membrane Electrode Assembly

Direct air capture (DAC) is a growing field responding to the need to remove carbon dioxide from the atmosphere. Several technologies are being developed today attempting to meet this need. The technology furthest in development are temperature swing adsorption technologies which have recently moved out of the pilot plant scale.1 This presentation looks to present an electrochemical device as alternative to these technologies. The electrochemical device proposed is a pair of nickel hydroxide (Ni(OH)2) battery electrodes which produce hydroxide (OH-). The hydroxide reacts with carbon dioxide (CO2) to create carbonate (CO32-) and bicarbonate (HCO3-). These carbonates can be transported from the cathode across an anion exchange membrane to the anode where they are evolved back into CO2 due to a pH reduction at the anode. This builds on work that optimized a Hydroxide Exchange Membrane Fuel Cell (HEMFC) for CO2 capture, showing the efficacy of an electrochemically mediated pH swing carbon capture device.2,3 The benefit of the nickel hydroxide battery approach is the low energy cost associated with separation. Because a pair of nickel hydroxide batteries undergo the same electrochemical reaction, low potentials, and thus low energy cost is required. Experiments have shown device level energy requirements of less than 1 MWh ton-1CO2. Most of the energy required by the device produces the pH gradient used to capture and release CO2. The biggest hurdle for this electrochemical approach is increasing the flux of CO2 to allow for more compact devices. Strategies for managing the transient charge and discharge behavior of the battery system will be discussed. Focus will be on improving flux to reduce the overall cost of the device.

Buchen, James↗
DOE OSTI2025

Advancing Neutrino Simulation Modeling with MARLEY: Insights from the NNSA-MSIIP Internship

Core-collapse supernovae are intense sources of tens-of-MeV neutrinos. However, there is no experimental data to validate the current event generator MARLEY (Model of Argon Reaction Low Energy Yields) that can model supernova neutrinos. To validate the model, I developed a new muon capture feature within the MARLEY simulation framework by coding key functions in C++, Python, and ROOT. I generated and analyzed one million simulated muon capture events and comparing the results to experimental data. To improve the model, I worked on optimizing the model’s parameters to improve its precision using statistical methods.

Wong, Baker [Fermilab]↗
DOE OSTI2022

In-Field Alpha Spectrometer Development FY2022 Mid-Year Report

In response to needs identified by the International Atomic Energy Agency (IAEA), Idaho National Laboratory (INL) has developed an In-Field Alpha Spectrometer (IFAS) to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF 6 ) at processing facilities, to perform field assessments to verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, developed at Pacific Northwest National Laboratory (PNNL), which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (as a dihydrate, UO 2 F 2 ·2H 2 O). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the course of this project INL, PNNL, Oak Ridge National Laboratory worked to optimize the SUDA sample design for alpha spectrometry, to optimize processes for manufacturing, loading, and shipping SUDA samples, and to allow the measurement of loaded SUDA samples. In fiscal year (FY) 2022 INL has bene investigating the reproducibility and measurement precision of IFAS measurements and the associated determination of uranium enrichment.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2023

Latency considerations for stochastic optimizers in variational quantum algorithms

Variational quantum algorithms, which have risen to prominence in the noisy intermediate-scale quantum setting, require the implementation of a stochastic optimizer on classical hardware. To date, most research has employed algorithms based on the stochastic gradient iteration as the stochastic classical optimizer. In this work we propose instead using stochastic optimization algorithms that yield stochastic processes emulating the dynamics of classical deterministic algorithms. This approach results in methods with theoretically superior worst-case iteration complexities, at the expense of greater per-iteration sample (shot) complexities. We investigate this trade-off both theoretically and empirically and conclude that preferences for a choice of stochastic optimizer should explicitly depend on a function of both latency and shot execution times.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Digital Miniature Cathode Ray Magnetometer

In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of operating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which then emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only records the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innovation lies in the combination of electron beam projection, CMOS imager scintillation-based detection, and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device’s utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe’s performance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.

Turqueti, Marcos↗
DOE OSTI2021

Rapid Laser Reactive Sintering of Garnet Li 6.1 La 3 Zr 2 Al 0.3 O 12 Solid-State Electrolyte

All solid-state lithium-ion batteries (ASSLIBs) have gained significant interest in recent years due to their wide range of applications, including mobile devices, electric vehicles, and grid storage. Garnet-type Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolyte (SSE) continues to be a significant player in the fabrication of ASSLIBs with excellent ionic conductivity on the order of 10 -3 S•cm -1 with the integration of dopants and sintering aids to assist conductivity and structural evolution during the sintering procedure. Traditional sintering techniques, such as solid-state sintering (SSS), have been proven to yield desirable crystal structures. However, the low ionic conductivity results from inferior microstructure, and lithium loss is a significant challenge. Recently, a relatively novel sintering process called rapid laser reactive sintering (RLRS) has shown great potential for achieving fully dense solid oxide electrolytes with less surface element loss, resulted in high ionic conductivity. Here, we applied the same RLRS method to fabricate LLZO dense electrolyte with different amounts of aluminum dopants. We hope the rapid high-temperature sintering can densify the electrolyte and avoid the lithium loss for achieving high lithium-ion conductivity. In this work, we optimized multiple combinations of laser parameters (speed, power, and defocus distance), initial precursor composition, and controlled atmospheres to discover the optimal conditions for reaching the efficacious crystal structure, microstructure, and ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2024

Third-integer Resonant Extraction Regulation System for Mu2e

A third-integer resonant slow extraction system is being developed for Fermilab's Delivery Ring to deliver protons to the upcoming Mu2e experiment. The timescale of the extraction (or spill) duration is 43 milliseconds, which is extremely short and unprecedented. Additionally, the experiment's strict and challenging requirements on the quality of the spill at this time scale has led to the development of a new Spill Regulation System (SRS) design. The SRS primarily consists of three components - slow regulation, fast regulation, and harmonic content suppressor. Contributions to the first two components of the SRS, i.e., Slow Regulation and Fast Regulation subsystems, will be presented in which new adaptive learning algorithm schemes for the slow regulation of the spill -- validated using particle tracking simulations -- shall be described. In addition to these novel methods for the enhancement of the spill regulation system, results of employing Machine Learning in enhancing the performance of the resonant extraction are also presented. At the forefront of applying ML techniques to solve non-linear accelerator control problems, this work includes optimizing the PID gains as well as the replacement of the traditional PID controller using Recurrent Neural Networks and Gated Recurrent Unit (GRU) ML models to achieve efficiencies greater than a PID controller. Cutting-edge on-going Reinforcement Learning efforts, including an actor-critic family of learning algorithms, to regulate the spill rate will be reviewed, as well as present analytical calculations pertaining the transit time of particles in a third-integer resonant extraction. Detailed numerical investigations and validations of such calculations, the model of which could be exported and reliably used in future analytical modeling of any resonant extraction, are discussed.

43 PARTICLE ACCELERATORS↗