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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

Low Temperature Tantalum Electrodeposition: Enabling Next Generation Coatings

This project aimed to identify the ligand and solvation conditions necessary for the electrodeposition of refractory metals from low-temperature organic electrolytes. Tantalum (Ta) was chosen as a specific exemplar for programmatic purposes. It was hoped that a deeper understanding of these relationships could facilitate the innovative application of refractory metal coatings on thermally sensitive and geometrically intricate components used in extreme environments related to energy generation and storage, nuclear deterrence, aerospace, defense, and beyond.

36 MATERIALS SCIENCE↗

The OSIRIS-REx Sample Return Capsule re-entry: A coordinated seismo-acoustic observational campaign for the study of meteor phenomena

Objects entering Earth’s atmosphere at hypersonic velocities may generate powerful acoustic waves. Depending on atmospheric conditions and acoustic propagation paths, they may be captured using ground or balloon-borne microbarometers and microphones. Impacts into the Earth’s atmosphere by asteroids in a meter-size range are sporadic and unannounced, and thus, well-documented scientific observations of asteroids are rare and generally happen by chance. Arriving from interplanetary space at hypervelocity, spacecraft are considered analogues for low velocity meteoroids and asteroids impacting the Earth’s atmosphere, and as such provide unprecedented and unique opportunity to carry out planned observational campaigns and perform detailed studies of meteor phenomena. However, since the end of the Apollo era, only four instances of a hypersonic re-entry of an artificial body from interplanetary space with an incident speed of 11-12 km/s have been observed and studied. These were the Sample Return Capsules (SRCs) that brought physical samples of extraterrestrial material back to Earth (Genesis, Stardust, Hayabusa 1, Hayabusa 2). These re-entries were also detected by infrasound and/or seismic sensors. The next opportunity to observe an artificial meteor will be on 24 September 2023 with the re-entry of NASA’s OSIRIS-REx SRC that will bring samples of the carbonaceous near-Earth asteroid Bennu. The re-entry consists of several flight phases, including hypersonic and supersonic, providing a unique opportunity to observe these by infrasound and seismic sensors. We will discuss observational campaign efforts aimed to capture geophysical signals generated by the OSIRIS-REx SRC re-entry. This campaign utilizes an unparalleled number of instruments, both ground and airborne, strategically positioned in the immediate and extended region around the projected re-entry trajectory to maximize the scientific output.

47 - OTHER INSTRUMENTATION↗

Stochastic Adaptive Droop Control in Frequency Regulation of Power Systems With Intermittent Generators

Modern power systems (MPSs), including microgrids (MGs), are increasingly incorporating multiple renewable energy sources (RESs) such as wind and solar power, as well as battery storage and controllable loads. While environmentally beneficial, these sources pose challenges for control and management due to their intermittent and stochastic nature, especially in maintaining frequency stability with multiple interconnected generators of varying capacities. Traditional droop control methods are effective in systems with generators that are dispatchable and have fixed generation capacities, but they fall short when applied to systems with RESs, where generation capacities are dynamic and affected by unpredictable environmental conditions. To address these challenges, this paper introduces a novel stochastic adaptive droop control (SADC) method for load frequency control (LFC). The proposed method adapts droop coefficients in real time, based on the measured stochastic data of power generation capacities, enabling more effective frequency regulation in systems with variable and intermittent power generation. Unlike traditional adaptive control methods, which assume constant or slowly-varying system parameters, this approach accounts for stochastic processes by modeling them as Markov chains, enabling robust performance under highly dynamic and unpredictable conditions. The key contributions of this work include the development of real-time droop coefficient adaptation algorithms, derivation of their stability and convergence properties, and the demonstration of the advantages of the method through simulations. Case studies highlight the improved performance of frequency regulation, particularly in addressing the impact of stochastic weather conditions and the benefits of reducing dependence on battery reserves in dealing with intermittency of RESs. Finally, this paper provides a comprehensive analysis of the theoretical foundations of the method, as well as practical implementation insights for future power systems with high penetration of RESs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Implicit quantile networks for emulation in jet physics

Abstract The ability to model and sample from conditional densities is important in many physics applications. Implicit quantile networks (IQN) have been successfully applied to this task in domains outside physics. In this work, we illustrate the potential of IQNs as components of emulators using the simulation of jets as an example. Specifically, we use an IQN to map jets described by their 4-momenta at the generation level to jets at the event reconstruction level. The conditional densities emulated by our model closely match those generated by Delphes , while also enabling faster jet simulation.

Kronheim, Braden (ORCID:0000000307040972)↗

Applying Particle Swarm Optimization and Extended Kalman Filtering to Model Kaplan Generation Dynamics for Hydropower Systems

Variable renewable generation is increasing the need for hydropower plants to provide fast and flexible grid support, which places new demands on plant-level dynamic models used for monitoring, control, and operational decision-making. This need is especially important for hydroelectric systems, where turbine and generator dynamics are strongly coupled, nonlinear, and time-varying, making accurate real-time representation difficult. To address this problem, this paper develops a digital twin (DT) framework for a synchronous generator–Kaplan turbine system using an explicit separation of slow turbine dynamics and fast generator dynamics. The turbine subsystem is represented by a six-coefficient model, whose parameters are identified offline using particle swarm optimization, while the generator subsystem is updated online through an extended Kalman filter for real-time state and parameter estimation. These models are integrated within a closed-loop simulation that includes a proportional–integral–derivative–double-derivative governor and excitation system, allowing the DT to track plant behavior under realistic operating conditions. Unlike prior studies that treat turbine and generator modeling separately or rely mainly on simulated inputs, the proposed framework is validated using real operational data from a hydropower plant. Results show that the DT reproduces terminal voltage, active power, and reactive power with a normalized root mean square error of approximately 5%. This hybrid offline–online formulation constitutes the main contribution of the work, providing an adaptive and practically deployable DT for hydropower systems with direct relevance to control improvement, performance monitoring, and grid-support applications under high renewable penetration.

13 HYDRO ENERGY↗

Direct numerical simulation of a high-pressure hydrogen micromix combustor: Flame structure and stabilisation mechanism

A high-pressure hydrogen micromix combustor has been investigated using direct numerical simulation with detailed chemistry to examine the flame structure and stabilisation mechanism. The configuration of the combustor was based on the design by Schefer et al., using numerical periodicity to mimic a large square array. A precursor simulation of an opposed jet-in-crossflow was first conducted to generate appropriate partially-premixed inflow boundary conditions for the subsequent reacting simulation. The resulting flame can be described as an predominantly-lean inhomogeneously-premixed lifted jet flame. Five main zones were identified: a jet mixing region, a core flame, a peripheral flame, a recirculation zone, and combustion products. The core flame, situated over the jet mixing region, was found to burn as a thin reaction front, responsible for over 85% of the total fuel consumption. The peripheral flame shrouded the core flame, had low mean flow with high turbulence, and burned at very lean conditions (in the distributed burning regime). It was shown that turbulent premixed flame propagation was an order-of-magnitude too slow to stabilise the flame at these conditions. Stabilisation was identified to be due to ignition events resulting from turbulent mixing of fuel from the jet into mean recirculation of very lean hot products. Ignition events were found to correlate with shear-driven Kelvin-Helmholtz vortices, and increased in likelihood with streamwise distance. At the flame base, isolated events were observed, which developed into rapidly burning flame kernels that were blown downstream. Further downstream, near-simultaneous spatially-distributed ignition events were observed, which appeared more like ignition sheets. The paper concludes with a broader discussion that considers generalising from the conditions considered here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An analysis of physics limited dispatch of nuclear renewable integrated energy systems using deep reinforcement learning and dynamic modeling

Previous approaches to dispatching nuclear integrated energy systems (NIES) have focused on the profitability and flexibility of these systems to operate on energy grids with highly variable pricing. However, due to the complexity involved in modeling and designing these systems, there has been less emphasis on ensuring that these dispatch strategies are physically achievable. It is imperative to develop methods that allow the system to remain within the desired NIES operating conditions and perform this based on realistic limited forecasted information. This research employs next generation artificial intelligence, namely deep reinforcement learning (DRL), and a dynamic system model written in Modelica to find a safe and profitable dispatch strategy for a solar nuclear hybrid design. The DRL agent is shown to find a novel dispatch strategy that manages both power ramping and power levels while respecting operational limits. This DRL-based dispatch is compared to other dispatching strategies including an optimal design solution from mixed integer linear programming (MILP). It is found that incorporating the physics of such a tightly coupled NIES limits the profitability of the MILP-based dispatch strategy. As a result, the MILP solution overestimates the design’s generated revenue. In contrast, DRL significantly reduces the number of breaches of safe operational conditions during energy arbitrage while maintaining profitability. Furthermore, this work paves the way for a more detailed assessment of NIES profitability and could be used to aid operator decisions on future NIES projects.

14 - SOLAR ENERGY↗

A high-temperature heat flux sensor using the transverse Seebeck effect in elemental rhenium

Heat flux sensors compatible with hot environments are critical to advance aerospace, materials, and energy generation technologies that cope with extreme thermal conditions. In this work, we report on the development and characterization of a high-temperature heat flux sensor using the transverse Seebeck effect in rhenium single crystals. The sensor leverages refractory alloys and ceramics compatible with temperatures exceeding 1000 °C. The heat flux sensor was characterized from room temperature to 500 °C using a temperature-controlled calibration facility. At constant temperature, the sensor’s voltage output is linear with respect to the absorbed heat flux. The responsivity of the sensor varies with temperature, from 1.3 μV/(W/cm 2 ) at room temperature to −3.2 μV/(W/cm 2 ) at 500 °C, increasing monotonically in magnitude after changing sign from positive to negative at approximately 300 °C. The experimental results are in good agreement with analytical predictions of the sensor’s temperature-dependent responsivity, which suggest a further increase in magnitude up to −7.4 μV/(W/cm 2 ) at 1000 °C. These results highlight the unique characteristics of rhenium as a TSE transducer. The design offers compatibility with a wide range of operating temperatures and yields a measurement sensitivity that increases as the environmental conditions become more challenging.

20 FOSSIL-FUELED POWER PLANTS↗

Controlling Product Selectivity in Photochemical CO 2 Reduction with the Redox Potential of the Photosensitizer

The ability to selectively reduce CO 2 to a particular product or mixture of products is expected to play a key role in mitigation strategies aiming to alleviate the devastating impact of this greenhouse gas in our climate and oceans. Among those, the production of liquid solar fuels from CO 2 and H 2 O will likely need cascade strategies involving multiple catalysts carrying out different functions. This will require that the catalysts doing the initial CO 2 reduction steps deliver the right product or products to downstream catalysts. CO, H 2 and formate are the most common products in CO 2 reduction by molecular catalysts. Here, in this work, we demonstrate control over the selectivity of C 1 products in photochemical CO 2 reduction with the same catalyst, simply by changing the redox potential of the photosensitizer and/or the water concentration. Turnover numbers for CO generation with one of the photosensitizers under anhydrous conditions reached 85,000, one of the largest values reported to date. A combination of experimental results and DFT calculations show that control of the selectivity is achieved, in part, due to the interplay between regimes under kinetic or thermodynamic control. These regimes are largely dictated by the proton sources and the CO 2 reduction byproducts generated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemistry of Sugar Formation in the Gas Phase: Following the Activated Aldehyde

Sugars are produced by living organisms, and are required building blocks for life as we know it, which raises the foundational question of how sugars formed in a prebiotic environment. The abiotic formose reaction produces sugars from formaldehyde, but our understanding of its initiation step remains murky, with chemists invoking the concept of an “activated aldehyde” to seed this reaction. Singlet hydroxycarbenes, high-energy isomers of aldehydes, were recently reported to facilitate sugar formation under cold, nonaqueous conditions relevant to interstellar environments. Here, we generate singlet methylhydroxycarbene ( 1 CH 3 –C̈–OH) from the photodissociation of pyruvic acid and experimentally measure its gas-phase reaction with d 4 -acetaldehyde using multiplexed photoionization mass spectrometry. The C 4 H 4 D 4 O 2 isomer d 4 -acetoin is the sole product, which we kinetically link to the reactant CH 3 –C̈–OH, and attribute to a carbonyl-ene formation mechanism. We see no evidence of 3-hydroxybutanal, the C–H insertion product expected in carbene chemistry. Using automated exploration we calculate stationary points on the potential energy surface and report master equation rate coefficients from T = 20–600 K, providing quantitative kinetics of this fast reaction for use in chemical models. The prereactive complex in this reaction is stabilized by both hydrogen bonding and electrophilic carbene C═O interactions. These effects create a short-range dynamical bottleneck for the reaction besides the long- and midrange barrierless bottlenecks. Combined with recent reports of 1 HC̈OH production from methanol photodissociation and pyruvic acid production in cold irradiated ices, this work provides evidence that singlet hydroxycarbene + aldehyde chemistry is a feasible path to prebiotic sugar formation.

aldehydes↗

Metal–support interactions in metal oxide-supported atomic, cluster, and nanoparticle catalysis

Supported metal catalysts are essential to a plethora of processes in the chemical industry. The overall performance of these catalysts depends strongly on the interaction of adsorbates at the atomic level, which can be manipulated and controlled by the different constituents of the active material (i.e., support and active metal). The description of catalyst activity and the relationship between active constituent and the support, or metal–support interactions (MSI), in heterogeneous (thermo)catalysts is a complex phenomenon with multivariate (dependent and independent) contributions that are difficult to disentangle, both experimentally and theoretically. So-called “strong metal–support interactions” have been reported for several decades and summarized in excellent review articles. However, in recent years, there has been a proliferation of new findings related to atomically dispersed metal sites, metal oxide defects, and, for example, the generation and evolution of MSI under reaction conditions, which has led to the designation of (sub)classifications of MSI deserving to be critically and systematically evaluated. These include dynamic restructuring under alternating redox and reaction conditions, adsorbate-induced MSI, and evidence of strong interactions in oxide-supported metal oxide catalysts. Here, we review recent literature on MSI in oxide-supported metal particles to provide an up-to-date understanding of the underlying physicochemical principles that dominate the observed effects in supported metal atomic, cluster, and nanoparticle catalysts. Critical evaluation of different subclassifications of MSI is provided, along with discussions on the formation mechanisms, theoretical and characterization advances, and tuning strategies to manipulate catalytic reaction performance. We also provide a perspective on the future of the field, and we discuss the analysis of different MSI effects on catalysis quantitatively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of hydropower availability on resource adequacy of the United States western interconnection

Hydropower is a key energy source in the western interconnection of the United States, comprising about 25% of the annual installed nameplate capacity in 2020. However, its generation is increasingly impacted by changing hydrological conditions, operational constraints, environmental factors, water availability, and aging dam infrastructure. Assessing hydropower availability and resource adequacy is valuable for shaping energy policies and infrastructure requirements. In this study we evaluate the sensitivity of resource adequacy in the Western Interconnection to the unavailability of hydropower plants, under a wide-ranging set of 16,384 hydropower loss scenarios derived from a combination of 14 major hydrologic regions. Although a complete loss of hydropower capacity in any region is unlikely, studying such scenarios helps in identifying hydrologic regions most critical for maintaining resource adequacy. So, we identify key hydrologic regions with disproportionately large adequacy impacts relative to their installed hydropower capacity and study compounding effects between regions using classification and regression trees. Even after controlling for total installed capacity, we find that hydropower resources in the Pacific Northwest contribute the most to interconnection-wide adequacy outcomes, with resources in Northern California and the Desert Southwest providing more moderate incremental contributions.

13 HYDRO ENERGY↗

Model America - 2022 Arizona Building Energy Simulation Results from ORNL's AutoBEM

This dataset contains energy simulation outputs using ORNL's AutoBEM, covering the summer months (June 1st to August 31st) (named by "county_name.csv") and full-year periods (in output_all_year.zip) for each county in Arizona, USA. The data package includes simulation results such as basic energy metrics and anthropogenic emissions estimates. Files are provided in .csv. These data were generated to analyze the impact of weather conditions on energy use and emissions across urban and rural environments in Arizona, aiming to support research on urban heat islands, energy efficiency, and building retrofitting strategies. The source data for this work include NASA POWER weather datasets and computational models run using AutoBEM (i.e., an automated, large-scale energy simulation tool leveraging OpenStudio/EnergyPlus). This dataset can assist researchers, urban planners, and policymakers in developing climate-resilient energy systems and understanding anthropogenic contributions to local environments.

54 ENVIRONMENTAL SCIENCES↗

Non-invertible symmetries in finite-group gauge theory

We investigate the invertible and non-invertible symmetries of topological finite-group gauge theories in general spacetime dimensions, where the gauge group can be abelian or non-abelian. We focus in particular on the 0-form symmetry. The gapped domain walls that generate these symmetries are specified by boundary conditions for the gauge fields on either side of the wall. We investigate the fusion rules of these symmetries and their action on other topological defects including the Wilson lines, magnetic fluxes, and gapped boundaries. We illustrate these constructions with various novel examples, including non-invertible electric-magnetic duality symmetry in 3+1d \mathbb{Z}_2 ℤ 2 gauge theory, and non-invertible analogs of electric-magnetic duality symmetry in non-abelian finite-group gauge theories. In particular, we discover topological domain walls that obey Fibonacci fusion rules in 2+1d gauge theory with dihedral gauge group of order 8. We also generalize the Cheshire string defect to analogous defects of general codimensions and gauge groups and show that they form a closed fusion algebra.

Córdova, Clay↗

Understanding and controlling water-organic co-transport in amorphous microporous materials

The transport of molecules in microporous material is a significant and active area of research in separation applications. The movement of vapor/liquid molecules in a high-loading condition in microporous spaces is especially challenging to interrogate. This project aims to understand and control the transport of complex water and organic solvent mixtures in varying structures of microporous carbon molecular sieve (CMS) and activated carbon membranes. Modeling of transport behavior in such carbonaceous samples using computational modeling is difficult due to their amorphous structure. Therefore, this research intends to study the transport mechanism of water-organic mixtures by experimentally revealing fundamental transport properties, such as guest sorption amounts as well as diffusion and permeation rates. Considering the different size and guest-host affinity of water and organic solvent molecules, the objective of this research is to understand the structural conditions within the ultramicropores and micropores that generate different types of molecular transport and selection mechanisms within such complex systems. Carbonaceous materials are developed using tailored pyrolysis techniques to pyrolyze polymeric precursors, including polyvinylidene chloride (PVDC),polyvinylidene fluoride (PVDF), polymer of intrinsic microporosity (PIM) -1, and fully aromatic polyamide. The initial stage of the research will focus on the microscopic diffusion and sorption studies of pure component water, xylene isomers, and n,n- dimethylformamide within various carbons. Additional structural investigation on CMS, such as gas physisorption and neutron scattering studies, will be executed to gain deeper insight into these structure-transport relationships. Scanning electron microscopy and X-ray photoelectron microscopy are also used to further characterize these materials. The research will progress to probe mutual diffusion of complex water-organic mixtures within various CMS microstructures. Competitive sorption and permeation studies of the binary mixtures in different microstructural CMS will be followed. The obtained binary mixture transport parameters were used to predict binary water-organic mixtures transport.

36 MATERIALS SCIENCE↗

Kinetic and Mechanistic Understanding of Boron-Containing Catalysts for the Production of Light Olefins through Selective Oxidation

In recent years, an abundance of natural gas obtained from shale deposits has created opportunities for the US chemical industry to establish new and more efficient processes for the production of chemical intermediates and polymers. For example, the replacement of petroleum-derived naphtha as a to shale-derived ethane as feedstocks has made the production of ethylene/polyethylene less costly. However, this shift in feedstock has led to lower production of propylene from steam crackers, and new “on-purpose” light olefin production technologies have been implemented to bridge the gap between propylene supply and demand. The most important of these processes is direct propane dehydrogenation (PDH), but catalyst deactivation and high temperatures lead to high capital and operating costs. Oxidative dehydrogenation of propane (ODHP) is an efficient alternative to PDH, but high selectivity to CO2 from previous metal oxide catalyst prevents implementation. Hexagonal boron nitride (hBN) and other boron-containing materials have been recently developed as highly selective catalysts for both ODHP and oxidative cracking, surpassing previous systems. Much is still unknown in regard to the mechanism and the dynamic surface changes that occur under reaction conditions. This research project aims to combine in situ/operando spectroscopic investigation and kinetic studies to elucidate the interplay between the proposed gas-phase mechanism and the surface structures on the working catalyst. These insights will be leveraged to create a framework for optimizing reaction conditions and material synthesis for the next generation of boron-containing selective oxidation catalysts.

02 PETROLEUM↗

Measurement of Close-in Ground Motion from an Underground Chemical Explosion

Understanding the geophysical response near an underground explosion is crucial for generating insights into the source and emplacement conditions that produce distinct observations in monitoring scenarios occurring at greater distances. Recently, Shot A of the Low Yield Nuclear Monitoring (LYNM) Physics Experiment 1 (PE1) series was conducted at the Nevada National Security Site to provide ground truth for subsurface explosion signal models. This experiment resulted in measuring near-source ground motion at distances ranging from 70 to 1000 m/kt with a 99% success rate, yielding high-fidelity knowledge of the near-field response that can serve as benchmarks for future numerical modeling and experiment planning. However, technical challenges exist in observing near-source phenomena while safeguarding sensitive data acquisition components from the detrimental effects of ground motion in the subsurface. This report outlines tools and techniques to address challenges associated with observing near-source accelerations and within the tunnel drift of the PE1 test bed. Additionally, we describe key systems designed with both modern advancements and legacy guidance to maximize the collection of high-quality ground motion data, which may be applied to constitutive and computational models, leading to new or improved understanding of the near- and far-field signals produced by underground explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Development of a High-Rate Lithium-Air Battery Using a Gaseous CO 2 Reactant

Li-air batteries are considered a potential alternative to Li-ion batteries for transportation applications due to their high theoretical specific energy. Most works in this area focus on use of O 2 as the reactant. However, newer concepts for using gaseous reactants (such as CO 2 , which has a theoretical specific energy density of 1,876 Wh/kg) provide opportunities for further exploration. The main objective of this project was the development of a novel strategy that enables operation of Li-CO 2 batteries at high-capacity and high-rate, with a long-cycle-life. The team was able to: (1) Synthesize two novel transition metal chalcogenide (TMC) catalysts that work in synergy with ionic liquid-based electrolytes to enhance the efficiency of reactions during discharge and charge processes; (2) Fabricate high-porosity cathode electrodes with 3D printing to increase electrode surface area and gas permeability; (3) Develop a multiscale modeling framework that integrates Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties of Li-CO 2 batteries; (4) Assemble a stackable Li-CO 2 pouch-cell able to deliver a capacity of >200 mAh. These achievements were realized through an integrated approach based on materials synthesis, testing, characterization, analysis, and computation. This project produced a thorough understanding of key chemical, electronic, and kinetic parameters that govern the operation of Li- CO 2 batteries in realistic conditions. The methodologies employed, and the insight generated, will be valuable beyond advancing the field of Li-CO 2 batteries

25 ENERGY STORAGE↗