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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 37 records · Page 2

Air-Sea Spray Airborne Radar Profiler Characterizes Energy Fluxes in Hurricanes

A report discusses ASAP (Air-sea Spray Airborne Profiler), a dual-wavelength radar profiler that provides measurement information about the droplet size distribution (DSD) of sea-spray, which can be used to estimate heat and moisture fluxes for hurricane research. Researchers have recently determined that sea spray can have a large effect on the magnitude and distribution of the air-sea energy flux at hurricane -force wind speeds. To obtain information about the DSD, two parameters of the DSD are required; for example, overall DSD amplitude and DSD mean diameter. This requires two measurements. Two frequencies are used, with a large enough separation that the differential frequency provides size information. One frequency is 94 GHz; the other is 220 GHz. These correspond to the Rayleigh and Mie regions. Above a surface wind speed of 10 m/ s, production of sea spray grows exponentially. Both the number of large droplets and the altitude they reach are a function of the surface wind speed.

Durden, Stephen L.↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis – Simulated Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wind turbine. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen . While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the simulated wind energy profiles, NLR used OpenFAST to simulate a 3.4-MW International Energy Agency (IEA) reference wind turbine. The hour-long wind energy profiles varied over wind turbulence intensity (Class A or Class C) and average wind speed (5, 7, or 9 m/s). To match the power limits of the 1.25-MW electrolyzer and 3.4-MW IEA wind turbine most effectively and to maximize the efficiency of hydrogen production at a given average wind speed, the profiles were sometimes scaled by two times. This means that, in some cases, the experimental setup assumed two 1.25-MW electrolyzers were coupled with the wind turbine, representing a total maximum electrolysis load of 2.5 MW. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}-{average wind speed}-{turbulence class}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “windIEA3.4-5ms-C_2-400.zip” represents the hour-long experiment using the IEA 3.4-MW turbine, subjected to an average wind speed of 5 m/s and Class C wind turbulence, and connected to two 1.25-MW electrolyzers with the power supply set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wind turbine power. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis .

08 HYDROGEN↗

Conference on Complex Turbulent Flows: Comparison of Computation and Experiment, Stanford University, Stanford, CA, September 14-18, 1981, Proceedings. Volume 2 - Taxonomies, reporters' summaries, evaluation, and conclusions

Computational techniques for simulating turbulent flows were explored, together with the results of experimental investigations. Particular attention was devoted to the possibility of defining a universal closure model, applicable for all turbulence situations; however, conclusions were drawn that zonal models, describing localized structures, were the most promising techniques to date. The taxonomy of turbulent flows was summarized, as were algebraic, differential, integral, and partial differential methods for numerical depiction of turbulent flows. Numerous comparisons of theoretically predicted and experimentally obtained data for wall pressure distributions, velocity profiles, turbulent kinetic energy profiles, Reynolds shear stress profiles, and flows around transonic airfoils were presented. Simplifying techniques for reducing the necessary computational time for modeling complex flowfields were surveyed, together with the industrial requirements and applications of computational fluid dynamics techniques.

Kline, S. J.↗

Commissioning of the neutron irradiation station at the University of Notre Dame

Cross section data for neutron-induced reactions are needed for applications in nuclear astrophysics, stockpile stewardship, and nuclear reactor design but often contain discrepancies and gaps. A neutron source with a high neutron flux, a well-characterized neutron energy distribution, and a wide range of available neutron energies is ideal for studying such reactions in order to improve on existing data and provide new experimental results. For this purpose, the Neutron Irradiation Station (NIS) was developed using the 7 Li(p,n) 7 Be reaction. Neutron energy profiles were obtained using 3 He spectrometers and neutron standards were used to determine the neutron flux using the activation method. The neutron energy profile was found to be quasi-monoenergetic and neutrons were produced at energies from 1 keV to 1 MeV. Finally, the flux at the production target was found to be (1.42 ± 0.20) x 10 8 s −1 cm −2 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Deciphering the Cofilin Oligomers via Intermolecular Disulfide Bond Formation: A Coarse-Grained Molecular Dynamics Approach to Understanding Cofilin’s Regulation on Actin Filaments

Cofilin, a key actin-binding protein, orchestrates the dynamics of the actomyosin network through its actin-severing activity and by promoting the recycling of actin monomers. Recent experimental work suggests that cofilin also forms functionally distinct oligomers through thiol post-translational modification (PTM) that encourages actin nucleation and assembly. Despite these advances, the structural conformations of cofilin oligomers that modulate actin activity remain elusive because there are combinatorial ways to oxidize thiols in cysteines to form disulfide bonds rapidly. This study employs molecular dynamics simulations to investigate human cofilin 1 as a case study for exploring cofilin dimers via disulfide bond formation. Using the free energy profiling, our simulations unveil a range of probable cofilin dimer structures not represented in current Protein Data Bank entries. These candidate dimers are characterized by their distinct population distributions and relative free energies. Of particular note is a dimer featuring an interface between cysteines 139 and 147 residues, which demonstrates stable free energy characteristics and intriguingly symmetrical geometry. In contrast, the experimentally proposed dimer structure exhibits a less stable free energy profile. Here, we also evaluate frustration quantification based on the energy landscape theory in the protein-protein interactions at the dimer interfaces. Notably, the 39-39 dimer configuration emerges as a promising candidate for forming cofilin tetramers, as substantiated by frustration analysis. Additionally, docking simulations with actin filaments further evaluate the stability of these cofilin dimer-actin complexes. Our findings thus offer a computational framework for understanding the role of thiol post-translational modification cofilin proteins in regulating oligomerization, and the subsequent cofilin-mediated actin dynamics in the actomyosin network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ion Channels – From Structure to Electrophysiology and Back

A reliable way to establish whether our understanding of a channel is satisfactory is to reproduce its measured ionic conductance over a broad range of applied voltages in computer simulations. In molecular dynamics (MD), this can be done by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. Since this approach is computationally very expensive, we have developed a markedly more efficient alternative in which MD is combined with the electrodiffusion (ED) equation. In this approach, the assumptions of the ED equation can be rigorously tested, and the precision and consistency of the calculated conductance can be determined. We have demonstrated that the full current/voltage dependence and the underlying free energy profile for a simple channel can be reliably calculated from equilibrium or non-equilibrium MD simulations at a single voltage. Free energy profiles can be obtained from non-equilibrium simulations without a loss of accuracy even without the knowledge of diffusion coefficient. To carry out MD simulations, a structural model of a channel has to be assumed, which is an important constraint, considering that high-resolution structures are available for only very few simple channels. If the comparison of calculated ionic conductance with electrophysiological data is satisfactory, it greatly increases our confidence that the structure and the function are described sufficiently accurately. We examined the validity of the ED for several channels embedded in phospholipid membranes - four naturally occurring channels: trichotoxin, alamethicin, p7 from hepatitis C virus (HCV) and Vpu from the HIV-1 virus, a synthetic, hexameric channel, formed by a 21-residue peptide that contains only leucine and serine and a bacterial pentameric ligand-gated ion channel, GLIC. All these channels mediate transport of potassium and chloride ions. It was found that the ED equation is satisfactory for these systems. In some of them, experimental and calculated electrophysiological properties are in good agreement, whereas in others there are strong indications that the structural models are incorrect.

Pohorille, Andrew↗

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗

Identification of Active Metal Carbide and Nitride Catalytic Facets for Hydrodeoxygenation Reactions

The catalytic hydrodeoxygenation (HDO) reaction is of considerable interest for biomass conversion to valuable chemicals and fuels, where one of the critical bottlenecks is the lack of cost-effective and efficient catalysts. To discover cost-efficient catalysts for the HDO reaction, we employed a density functional theory-based hierarchical catalyst design strategy based on catalytic descriptors, reaction energy profiles, and microkinetic modeling (MKM). We focused on the carbide and nitride catalyst space, for which we calculated 121 catalyst surfaces of Mo 2 C, MoC, Mo 2 N, W 2 C, NbC, VC, VN, and NbN catalysts. Based on the computed surface energies, reaction energies of oxygen removal, carbon binding strength, and the surface area of nanoparticles, the likely active facets are the Mo 2 C(111), MoC(011), VN(100), Mo 2 N(001), Mo 2 N(011), and Mo 2 N(100) surfaces. Further, detailed energy profiles were obtained, and MKM was performed for a model reaction (glycolaldehyde + 2H 2 . ethylene + 2H 2 O) on the Mo 2 C(111), VN(100), and MoC(100) surfaces. Based on the computed volcano map obtained from MKM, the predicted active facets for this HDO reaction are the Mo 2 C(111), MoC(011), VN(011), Mo 2 N(001), Mo 2 N(011), and Mo 2 N(100) surfaces. Additionally, none of the carbide and nitride catalyst surfaces are located in the optimal catalytic activity part. Therefore, it is essential to modify the catalyst via adding dopants or alloying to improve the catalytic activity. Catalytic modifications that can destabilize the surface adsorption of O*/H 2 O* and decrease the energy barriers of O-H bond formation are recommended to facilitate the HDO on the carbide and nitride catalysts. These a priori investigations provide guidelines for future low-cost HDO catalyst development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Total Energy Deposition Between Periodically Occurring Activations of the Aurora

Total energy deposition in the northern latitudes is used in models to determine the state of the magnetosphere. It is known that on occasion, a series of intensifications of the aurora occur that are regularly spaced. The energy profile of the total energy deposited reflects this occurance. What can be said of the state of the magnetosphere based on these profiles. We present the result of a study which looks at several of these periods when a series of intensifications occur. Conclusions as to what the magnetosphere may be doing are presented.

Spann, James F., Jr.↗

Cobalt-Group 13 Complexes Catalyze CO 2 Hydrogenation via a Co(-I)/Co(I) Redox Cycle

The Co(-I) dihydrogen complexes, [(η 2 -H 2 )CoML]-, where ML is the group 13 metalloligand, N(o-(NCH 2 PiPr 2 )C 6 H 4 ) 3 M, and M is Al, Ga, or In, were previously reported ( J. Am. Chem. Soc. 2017, 139, 6570-6573). In this work, the related Co(-I) end-on dinitrogen adducts, [(N 2 )CoML]-, were isolated and investigated as precatalysts for CO 2 hydrogenation. The Co–Ga catalyst was highly active, achieving 19,200 formate turnovers with an initial turnover frequency of 27,000 h –1 under 34 atm of 1:1 CO 2 /H 2 and using Verkade’s proazaphosphatrane as a base at ambient temperature. The Co–Al catalyst was moderately active, while the Co–In complex was inactive. Hence, tuning the group 13 ion greatly influences the catalytic activity at the Co site. To elucidate the role of the group 13 support, experimental and theoretical mechanistic studies of the Co–Ga and Co–Al catalysts were conducted. The Co(-I) H 2 species are potent hydride donors with estimated thermodynamic hydricities (ΔG° H– ) of 32.0(1) and 37.4(1) kcal/mol in CH 3 CN for M = Al and Ga, respectively. By acting as masked Co(I) dihydrides, the Co(-I) H 2 species operate via an unusual Co(-I)/Co(I) redox cycle. After hydride transfer to CO 2 , the resulting intermediate is the Co(I) hydride complex, HCoML, which was independently synthesized and structurally characterized for M = Al and Ga. The Gibbs free energy for H 2 binding, ΔG° bind (1 atm), to generate (η 2 -H 2 )HCoML was slightly more favorable for HCoGaL (-4.2(1) kcal/mol) than for HCoAlL (-2.7(1) kcal/mol). In the subsequent step, the deprotonation reaction to regenerate the initial catalyst was much more favorable for (η 2 -H 2 )HCoGaL (pK a of 31.4, CH 3 CN) than for (η 2 -H 2 )HCoAlL (pK a of 34.3). Finally, the straightforward substitution of Al with Ga perturbs the energy profile of the catalytic reaction (|ΔΔG° H– | = 5.4 kcal/mol, |ΔΔG° bind | = 1.5 kcal/mol, and |ΔΔG° K a | = 4.0 kcal/mol) and thus provides a thermodynamic rationale for the higher catalytic efficiency of Co–Ga over Co–Al.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of the depth of maximum of air-shower profiles with energies between 10 18.5 and 10 20 eV using the surface detector of the Pierre Auger Observatory and deep learning

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV ( 1 EeV = 10 18 eV ) using the distributions of the depth of shower maximum X max . The analysis relies on ∼ 50 , 000 events recorded by the surface detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the dataset offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the fluorescence detector, this enables the first measurement of the evolution of the mean and the standard deviation of the X max distributions up to 100 EeV. Our findings are threefold: (i) The evolution of the mean logarithmic mass toward a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (ii) The evolution of the fluctuations of X max toward a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in X max at the highest energies. (iii) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum. Published by the American Physical Society 2025

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mechanistic Insights into Oxygen Reduction Reaction on Metal Cathode Over BaZrO 3 -Based Electrolyte under Moist Atmosphere: Interfacial Interactions and Reaction Pathways

The oxygen reduction reaction (ORR) is a critical process that often governs the overall performance of electrochemical systems such as proton conducting solid oxide fuel cells. Despite its significance, the current understanding about the ORR, especially when it involves H 2 O is still limited. In this study, the proton involved ORR (PI-ORR) on metal cathode (e.g., Pt) over BaZrO 3 (BZO) electrolyte is investigated using density functional theory (DFT) under moist atmosphere. Two scenarios are considered: one at relatively high temperature (900 K) in the presence of oxygen vacancy in BZO substrate and one at relatively low temperature (700 K) without oxygen vacancy. We systematically explored oxygen vacancy effects on adsorption sites and proton transfer pathways, calculated energy profiles and Gibbs free energies for elementary steps along the O 2 dissociated and the O 2 concerted reaction pathways. We also evaluated H 2 O impacts on intermediate oxygen species (*O and *OH) through Ab Initio molecular dynamics. These analyses revealed pathway-dependent reaction mechanisms and hydration effects at triple-phase boundary, advancing fundamental understanding of PI-ORR in metal cathode/Ba-based electrolyte systems for energy applications.

08 - HYDROGEN↗

Effects of aircraft and flight parameters on energy-efficient profile descents in time-based metered traffic

Concepts to save fuel while preserving airport capacity by combining time based metering with profile descent procedures were developed. A computer algorithm is developed to provide the flight crew with the information needed to fly from an entry fix to a metering fix and arrive there at a predetermined time, altitude, and airspeed. The flight from the metering fix to an aim point near the airport was calculated. The flight path is divided into several descent and deceleration segments. Descents are performed at constant Mach numbers or calibrated airspeed, whereas decelerations occur at constant altitude. The time and distance associated with each segment are calculated from point mass equations of motion for a clean configuration with idle thrust. Wind and nonstandard atmospheric properties have a large effect on the flight path. It is found that uncertainty in the descent Mach number has a large effect on the predicted flight time. Of the possible combinations of Mach number and calibrated airspeed for a descent, only small changes were observed in the fuel consumed.

Dejarnette, F. R.↗

Effects of aircraft and flight parameters on energy-efficient profile descents in time-based metered traffic

Attention is given to a computer algorithm yielding the data required for a flight crew to navigate from an entry fix, about 100 nm from an airport, to a metering fix, and arrive there at a predetermined time, altitude, and airspeed. The flight path is divided into several descent and deceleration segments. Results for the case of a B-737 airliner indicate that wind and nonstandard atmospheric properties have a significant effect on the flight path and must be taken into account. While a range of combinations of Mach number and calibrated airspeed is possible for the descent segments leading to the metering fix, only small changes in the fuel consumed were observed for this range of combinations. A combination that is based on scheduling flexibility therefore seems preferable.

Dejarnette, F. R.↗

Effects of aircraft and flight parameters on energy-efficient profile descents in time-based metered traffic

The influence of several parameters on the time required to fly a nominal profile descent of a B-737 from an entry fix to a metering fix 75 n.mi. away was studied. The ground distance for the constant speed segment was adjusted in each case so that the aircraft would always arrive at the metering fix position at the completion of the five segments of the profile descent. The influence of eight parameters on the same nominal profile descent is outlined, but the method used for the off nominal cases was changed. The time calculated for the constant speed segment in the nominal case is used for all off nominal cases. This method allows the aircraft to arrive at the metering fix before or after the profile descent is complete. It is shown that descent Mach number and wind speed have a large effect on the time error, whereas weight was a much smaller effect.

Dejarnette, F. R.↗

Energy management system, method of controlling one or more energy storage devices and control unit for one or more power storage units

Systems, methods and apparatuses are provided for reducing peak energy demand and to smooth intermittent energy profiles from onsite variable energy sources and loads. Some embodiments use system level and device level analysis and optimization to adaptively adjust the operation of a behind the meter energy storage (BMES) to smooth out energy generation variabilities and follow a reference load signal, including at short time resolutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Life cycle energy demand and carbon emissions of scalable single-junction and tandem perovskite PV

Perovskite photovoltaics reached record efficiencies in the laboratory and, if sustainably commercialized, they would accelerate a green energy transition. Here, this article presents the development of life-cycle inventory material and energy databases of most promising four single-junction and three tandem scalable perovskite systems with assumptions regarding scalable production validated by industry experts. We conducted comprehensive “ex ante” Life Cycle Analysis (LCA) and Net Energy Analysis, analyzing their cumulative energy demand, global warming potential profiles, energy payback times and energy return on investment (EROI). LCA contribution analysis elucidates the most impactful material and process choices. It shows that solution-based perovskite manufacturing would have lower environmental impact than vapor-based methods, and that roll-to-roll (RtR) printing offers the lowest impact. Among material choices, MoOx/Al has lower impact than Ag, and fluorine-tin-oxide lower than indium-tin-oxide. Furthermore, we compare perovskites with commercial crystalline-silicon and thin-film PV, accounting for the most recent developments in crystalline-Si wafer production and differences in life expectancies and efficiencies. It is shown that perovskite systems produced with RtR manufacturing could reach in only 12 years of life the same EROI as that of single-crystalline-Si PV lasting 30-years. This work lays a foundation for sustainability investigations of perovskite large-scale deployment.

14 SOLAR ENERGY↗