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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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UV-Vis spectroscopy and PL data show that structural incorporation of Eu 3+ has an effect on the optical properties of CdSe QDs via energy transfer from host to dopant. This allows for QDs with tunable optical properties via numerous pathways.
Multifidelity modeling is a technique for fusing the information from two or more datasets into one model. It is particularly advantageous when one dataset contains few accurate results and the other contains many less accurate results. Within the context of modeling potential energy surfaces, the low-fidelity dataset can be made up of a large number of inexpensive energy computations that provide adequate coverage of the N-dimensional space spanned by the molecular internal coordinates. The high-fidelity dataset can provide fewer but more accurate electronic energies for the molecule in question. Here, we compare the performance of several neural network-based approaches to multifidelity modeling. We show that the four methods (dual, Δ-learning, weight transfer, and Meng–Karniadakis neural networks) outperform a traditional implementation of a neural network, given the same amount of training data. We also show that the Δ-learning approach is the most practical and tends to provide the most accurate model.
Broadband pump–probe spectroscopy has been widely used to measure vibrational decoherence associated with the reaction coordinate in photoinduced ultrafast vibration-coupled electron transfer (VCET) reactions. These experiments provide insight into the interplay of intramolecular coordinates along the reaction coordinate. However, a general theoretical foundation for analyzing, and even for explaining rigorously, these data is lacking. In this work, we study vibrational decoherence in a model VCET reaction using the nearly exact time-dependent density matrix renormalization group simulation method. We explore how analyzing the density matrix with quantum information measures can help elucidate the evolution of vibrational coherence in simulations of dynamics. We examine how vibrational coherence is affected by electron transfer on the timescale of approximately 100 femtoseconds. Our results suggest that electron transfer, in the nonadiabatic model, changes the vibrational equilibrium position abruptly—an example of a “quantum quench” event. This explains the concomitant vibrational decoherence. We find that abrupt vibrational decoherence can be mitigated by wavepacket motion occurring on the timescale of the electron transfer.
A framework for A(d, p)B reactions is introduced by merging the microscopic approach to computing the properties of the nucleon-target systems and the three-body n + p + A reaction formalism, thus providing a consistent link between the reaction cross sections and the underlying microscopic structure. In this first step toward a full microscopic description, we focus on the inclusion of the neutron-target microscopic properties. The properties of the neutron-target subsystem are encapsulated in the Green's function which is computed with the coupled Cluster theory using a chiral nucleon-nucleon and three-nucleon interactions. Subsequently, this many-body information is introduced in the few-body Green's Function Transfer approach to (d, p) reactions. Our benchmarks on stable targets 40,48 Ca show an excellent agreement with the data. We then proceed to make specific predictions for (d, p) on neutron rich 52,54 Ca isotopes. These predictions are directly relevant to testing the new magic numbers N = 32, 34 and are expected to be feasible in the first campaign of the projected FRIB facility.
The International Commission on Radiological Protection (ICRP) is updating its biokinetic models in a series of reports titled Occupational Intakes of Radionuclides (OIR series). This paper provides an overview of biokinetic data for the group IVB elements hafnium (Hf) and titanium (Ti), compares these data with findings for the more extensively studied Group IVB element zirconium (Zr), and proposes biokinetic models for systemic Hf and Ti for use in the OIR series. A biokinetic model for systemic Zr recently adopted by the ICRP is proposed for application to Hf in view of the nearly identical chemical and physical properties of these two elements, their closely similar behavior in the environment, and their nearly identical biokinetic properties suggested by available comparative data. Finaly, the model structure applied to Zr and Hf is also applied to Ti, but a separate set of transfer coefficients is proposed for Ti.
When spin-orbit torques are measured using spin-torque ferromagnetic resonance, two alternative ways of analyzing the results to extract the torque efficiencies—lineshape analysis and analysis of the change in linewidth versus direct current—often give inconsistent results. We identify a source for these inconsistencies. We show that fits of spin-torque ferromagnetic resonance data to the standard analysis framework leave significant residuals that we identify as due to (i) current-induced excitations of a small volume of magnetic material with magnetic damping much larger than that of the bulk of the magnetic layer, which we speculate is associated with the heavy-metal–magnet interface and (ii) oscillations of the sample magnetization at the modulation frequency due to heating. Here, the dependence of the residual signals on direct current can interfere with an accurate extraction of spin-torque efficiencies by the linewidth method. We show that the discrepancies between the two types of analysis can be largely eliminated by extrapolation of the window of magnetic fields used in the linewidth fits to small values so as to minimize the influence of the residual signals.
Microstructural heterogeneities arising from molecular clusters directly affect the nonlinear thermodynamic properties of supercritical fluids. We present a physical model to elucidate the relation between energy exchange and heterogeneous cluster dynamics during the transition from liquidlike to gaslike conditions. By analyzing molecular-dynamics data and employing physical principles, the model considers contributions from three key processes, namely, changing cluster density, cluster separation, and transfer of molecules between clusters. We show that the proposed model is consistent with the energetics at subcritical conditions and can be used to explain the nonlinear behavior of thermodynamic response functions, including the peak in the isobaric heat capacity.
Palladium membranes and membrane reactors can separate and purify tritium from impurities in the plasma exhaust processing system for the fusion energy fuel cycle. Membranes can also act as a continuous separation method to remove tritium from helium streams in the breeder blanket tritium extraction system, such as from the purge gas of solid breeders. To investigate the potential of these membranes for these applications, we performed a deuterium permeation campaign with a self-supported palladium-silver (Pd-25Ag wt%) tube of 0.15 m length, 76 µ m wall thickness, and 3.0 mm inner diameter. A gas mixture of 3.95% D 2 and a balance of He was delivered to the inside of the tube and D permeated radially outwards through the membrane into a vacuum chamber. Permeation experiments were conducted at 300 ° C, 350 ° C, 400° C, and 450°C, from 100 to 1000 sccm total flow rate, and with total pressures of 90, 150, 190, and 250 kPa. Further, deuterium permeation was consistently lower than predicted from diffusion-limited permeation models, thus we developed a transport model that included gas-phase mass transfer and surface reactions to model experimental results. The dissociation constant was optimized to fit the developed model to experimental data.
Abstract Many of the studies on the entropy‐stabilized oxide (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O have been heavily application‐based. Previous works have studied effects of cation stoichiometry on the entropy‐driven reaction to form a single phase, but a fundamental exploration of the effects of anion stoichiometry and/or redox chemistry on electrical properties is lacking. Using near‐edge X‐ray absorption fine structure (NEXAFS) and electrical measurements, we show that oxidizing thin film samples of (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O affects primarily the valence of Co, leaving the other cations in this high‐entropy system unchanged. This oxidation increases electrical conduction in these thin films, which occurs via small polaron hopping mediated by the Co valence shift from 2+ to a mixed 2+/3+ state. In parallel, we show that bulk samples sintered in an oxygen‐rich atmosphere have a lower activation energy for electrical conduction than those equilibrated in a nitrogen (reducing) atmosphere. Combining feasible defect compensation scenarios with electrical impedance measurements and NEXAFS data, we propose a self‐consistent interpretation of Co redox‐mediated small polaron conduction as the dominant method of charge transfer in this system.
Anthropogenic nitrogen input is the leading cause of increasing marine eutrophication. Cultivating seaweeds at large scales may provide a viable solution for mitigating eutrophication especially when nitrogen extraction is achieved as an added environmental benefit of biofuel and food production. As the first step to promoting and implementing this solution, it is critical to quantify and assess the effectiveness of nitrogen removal by existing seaweed farms. Pacific Northwest National Laboratory and Hood Canal Mariculture Inc. conducted a case study by applying a coupled modeling-monitoring approach to quantify nitrogen bioextraction by a one-hectare commercial sugar kelp farm in Hood Canal, WA. Through this two-year effort, the project team conducted intensive field monitoring of water quality parameters at the farm site and subsequent laboratory analysis. Meanwhile, the team applied a coupled hydrodynamic-macroalgal growth model to simulate kelp growth and nitrogen bioextraction over the two kelp growing seasons. The model results showed an overall good comparison with field monitoring data and showed the effectiveness of nitrogen removal by kelp farms. The established modeling-monitoring approach can also be transferable for supporting broader research activities in macroalgal farming and eutrophication mitigation.
Under direction from the DOE Office of Electricity, Sandia National Laboratories performed testing of the Viziv system to evaluate the quality of the Zenneck surface wave and potential application to long range power transfer. This report documents the test methodology as well as the test results. This includes an analysis of prior test data collected by Viziv.
Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.
Engine knock and misfire are barriers to pathways leading to high-efficiency Spark-Ignited (SI) Natural Gas (NG) engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by the low emission limits and the wide range of chemical reactivity in pipeline-quality natural gas. Depending on the region and the source of the natural gas, its reactivity, described by its Methane Number (MN), which is analogous to the Octane Number for liquid SI fuels, can span from 65 to 95. In order to realize diesel-like efficiencies, SI NG engines must be designed to operate at high Brake Mean Effective Pressures (BMEP), near or beyond knock limits, over a wide range of fuel reactivity. This requires a deep understanding of the combustion-engine interactions pertaining to flame propagation and End-Gas Autoignition (EGAI), i.e., the autoignition of the unburned gas (end gas) ahead of the flame front. However, EGAI, if controlled, provides an opportunity to increase SI NG engine efficiency by increasing the combustion rate and the total fraction of burned fuel, mitigating the effects of the slow flame speeds characteristic of natural gas fuels, which generally reduce BMEP and increase unburned hydrocarbon emissions. For this reason, to realize diesel-like efficiencies and ultra-low emissions on SI NG engines, this work proposes the study of the main parameters influencing the modeling and prediction of NG EGAI to allow for its control. In this work, a novel EGAI detection and onset determination method was developed to reliably quantify EGAI for data analysis and engine control. The new method allowed the prediction of EGAI on SI NG engines without the need to use engine- and operating-condition-dependent thresholds and reduced the error in quantifying the fraction of the total energy released by the EGAI event by up to 40%pts. One- and three-dimensional engine models were then developed to study the engine/fuel interactions that lead to NG EGAI and its performance benefits. These models, although having decent agreement with experimental data, showed the need to account for NOx chemistry when predicting NG EGAI due to a consistently later prediction of the EGAI onset (~1.65 crank-angle degrees) and thus, a new reduced chemical mechanism for real NG fuels was developed containing NOx chemistry. The new reduced mechanism improved the EGAI onset prediction agreement to within ±0.5 crank-angle degrees and decreased simulation time during combustion by nearly 50% when using the further reduced AREIS50NOx chemical mechanism. These models were then used to study the role of NG composition on EGAI, evaluate the engine/fuel interactions leading to NG EGAI, and perform engine optimization while leveraging EGAI to increase thermal efficiency. Piston design optimization combined with a Controlled EGAI (C-EGAI) combustion mode allowed a Heavy-Duty (HD) SI NG engine to operate at diesel-like efficiencies, i.e., Brake Thermal Efficiency (BTE) ≥44%. Experimental and modeling data analysis revealed that earlier and faster heat release increases combustion efficiency by an average of 1%pts, increases work transferred to the piston resulting in a decrease in exhaust losses by 50% depending on the engine operating condition while slightly increasing heat losses. Finally, the simulation results revealed an opportunity to further enhance the BTE (up to 50%) by enabling C-EGAI combustion at leaner conditions, λ=1.4-1.6.
This white paper evaluates the potential of a new energy system configuration: Strategic colocation of data centers - on airport property or adjacent to airports - in order to realize significant operational, economic, and environmental benefits to airports, data centers, and the communities they serve. While increasing demand from both airports and data centers requires both parties to make significant infrastructure investments, colocation can mitigate some of the energy, land use, permitting, and connectivity challenges of siting and powering these industries.
The research program developed, validated and applies predictive computational protocols for calculating charge transfer (CT) rates in complex molecular systems, including molecular dyads and triads in liquid solution and solid-state organic semiconducting (OSC) materials. We have established a transformative computational scheme that goes beyond widely used simplifications, to achieve realistic descriptions of CT processes. The approach properly addresses the contribution of molecular environment at ambient conditions to CT processes. Our approach achieves unique insight on investigated CT processes in relevant experimental efforts. The collaborative team included three principal investigators (PIs), with complimentary expertise in classical molecular dynamics simulations and data science (Cheung), state-of-the-art electronic structure calculations (Dunietz), and cutting-edge theory and simulation techniques for modeling energy, charge and coherence transfer dynamics in molecular systems (Geva).
Photochemical upconversion (UC) through triplet–triplet annihilation (TTA), which employs a visible absorbing triplet photosensitizer and an annihilator, is a process that generates a high energy photon from two lower energy photons. TTA-UC has been largely developed in pure organic solvents and solid-state polymeric constructs while featuring near exclusive use of rare and expensive metals within the photosensitizer. In this current investigation, we demonstrate that TTA-UC from the long lifetime earth-abundant photosensitizer [Cu(dsbtmp) 2 ](PF) 6 (dsbtmp = 2,9-di(sec-butyl)-3,4,7,8-tetramethyl-1,10-phenanthroline), abbreviated as Cu-PS, functions in water through encapsulation within a cationic-based assembly. Cetyltrimethylammonium bromide was the surfactant of choice as it electrostatically binds the negatively charged water-soluble 10-phenylanthracene-9-carboxylate (PAC) acceptor/annihilator and ultimately facilitates energy transfer across the interface. Efficient triplet–triplet energy transfer (TTET) from Cu-PS to the PAC acceptor was achieved in this aqueous assembly. Unfortunately, the hindered mobility of the PAC moieties ultimately hampered the annihilation process, and this was reflected in attenuated TTA rates and efficiencies. The combined experimental data illustrated that the water-soluble PAC acceptor was able to vectorially deliver the excited-state energy stored in Cu-PS across the interface into the bulk aqueous solution by engaging in excited-state electron transfer with methyl viologen acceptors. Lastly, these results are important for remotely operating photoredox reactions in water while rendering a photosensitizer spatially isolated in the hydrophobic core of a micelle.
This article presents the results of transient dynamic simulations of loads due to disruption eddy currents on the NSTXU vacuum vessel. Dynamic loading at diagnostic mounting locations is expressed as response spectra derived from the time history results of the dynamic structural simulations of a variety of disruption scenarios. The disruption simulations draw on a history of the project assessments of worst case disruptions for specific components. Major efforts to assess disruption loading have included the vacuum vessel which is the major structural support for the machine, as well as the passive plates (PPs), high harmonic fast wave (HHFW) antenna, and centerstack casing. Each one of these efforts included transient electromagnetic simulations producing time-dependent eddy current Lorentz loads (and in some cases halo loads) which then were applied to time-dependent structural dynamic analyses intended to obtain the proper dynamic amplification factors. In some instances, the EM model and structural model were identical allowing direct transfer of EM forces to the structural model. In other cases, the EM and structural model were not identical and the vector potential (VP) transfer method was used. The results files from these analyses were available (or re-run) to post process in ANSYS Classic time history postprocessor. In conclusion, the ANSYS command is used to create response spectra from time history data at desired points on the vessel.
We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.