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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Advancing X-ray quantum imaging through Monte-Carlo simulations

Imaging with X-rays poses fundamental limits due to radiation damage of the highly energetic photons. This becomes problematic for sensitive biological systems such as subcellular structures. Lowering the radiation dose, without sacrificing the signal-to-noise ratio, would be desirable for any kind of imaging modalities involving X-rays. To achieve this goal, quantum imaging with entangled X-ray photons constitutes a promising route. Production of biphotons have been demonstrated in the X-ray regime by the process of Spontaneous Parametric Down-Conversion (SPDC). However, compared to SPDC in the regime of visible light, the production rate for X-ray biphotons is extremely low. With the introduction of new high average brightness X-ray sources, such as 4th generation synchrotrons and high repetition rate Free-Electron X-ray Lasers (XFEL), quantum imaging may become practical. We introduce a ray tracing approach using Monte-Carlo sampling, specifically designed for quantum imaging with entangled X-ray photons generated by SPDC. By simulation, the superior image quality of quantum over classical imaging methods is demonstrated using realistic experimental conditions available at high repetition rate XFELs. With these simulations, we can efficiently assist the design of future experiments at beam lines, which can substantially accelerate the advancement of X-ray quantum imaging and reduce costs.

Entangled Photons↗
DOE OSTI2025

Critical insights into the steam electrolysis electrode in protonic ceramic cells for hydrogen production

Intermediate-temperature protonic ceramic electrolysis cells (PCECs), which combine the benefits of both lower- and higher-temperature electrolysis, are among the most efficient technologies for the production of green hydrogen. To ensure economic competitiveness and broad adoption, ongoing innovations in cell materials are essential to improve durability and reduce costs. The water oxidation half-reaction at the anode is a key area for improvement as it is a major contributor to performance degradation and efficiency loss in PCECs. Current anode designs, which are largely derived from solid oxide electrolysis cells, fail to address the specific requirements for PCECs under realistic operating conditions. Here, this Perspective highlights the unique challenges faced by PCEC anodes, focusing on the impact of high steam concentrations and the critical role of proton-coupled electron-transfer mechanisms—factors that are absent in solid oxide electrolysis cells. Furthermore, we explore design principles for advancing anodes tailored for PCECs, offering guidance for future research and development in this promising field.

Electrocatalysis↗
DOE OSTI2023

Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Generalized single excitation configuration interaction: an investigation into the impact of the inclusion of non-orthogonality on the calculation of core-excited states

In this paper, we investigate different non-orthogonal generalizations of the configuration interaction with single substitutions (CIS) method for the calculation of core-excited states. Fully non-orthogonal CIS (NOCIS) has been described previously for species with singlet and doublet ground states, and this paper reports the extension to molecules in their triplet ground state. In addition to NOCIS, we present a novel method, one-center NOCIS (1C-NOCIS), for open-shell molecules which is intermediate between NOCIS and the computationally less demanding static exchange approximation (STEX). We explore this hierarchy of spin-pure methods for core excitations of molecules with singlet, doublet, and triplet ground states. We conclude that, while NOCIS provides the best results and preserves the spatial symmetry of the wavefunction, 1C-NOCIS retains much of the accuracy of NOCIS at a dramatically reduced cost. For molecules with closed-shell ground states, STEX and 1C-NOCIS are identical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hyperconjugation-controlled molecular conformation weakens lithium-ion solvation and stabilizes lithium metal anodes

Tuning the solvation structure of lithium ions via electrolyte engineering has proven effective for lithium metal (Li) anodes. Further advancement that bypasses the trial-and-error practice relies on the establishment of molecular design principles. Expanding the scope of our previous work on solvent fluorination, we report here an alternative design principle for non-fluorinated solvents, which potentially have reduced cost, environmental impact, and toxicity. By studying non-fluorinated ethers systematically, we found that the short-chain acetals favor the [gauche, gauche] molecular conformation due to hyperconjugation, which leads to weakened monodentate coordination with Li + . The dimethoxymethane electrolyte showed fast activation to >99% coulombic efficiency (CE) and high ionic conductivity of 8.03 mS cm -1 . The electrolyte performance was demonstrated in anode-free Cu$∥$LFP pouch cells at current densities up to 4 mA cm -2 (70 to 100 cycles) and thin-Li$∥$high-loading-LFP coin cells (200–300 cycles). Overall, we demonstrated and rationalized the improvement in Li metal cyclability by the acetal structure compared to ethylene glycol ethers. We expect further improvement in performance by tuning the acetal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Probing the optical properties and toxicological profile of zinc tungstate nanorods

Zinc tungstate is a semiconductor known for its favorable photocatalytic, photoluminescence, and scintillation properties, coupled with its relatively low cost, reduced toxicity, and high stability in biological and catalytic environments. In particular, zinc tungstate evinces scintillation properties, namely the ability to emit visible light upon absorption of energetic radiation such as x rays, which has led to applications not only as radiation detectors but also for biomedical applications involving the delivery of optical light to deep tissue, such as photodynamic therapy and optogenetics. Here, we report on the synthesis of zinc tungstate nanorods generated via an optimized but facile method, which allows for synthetic control over the aspect ratio of the as-synthesized anisotropic motifs via rational variation of the solution pH. Additionally, we investigate the effect of aspect ratio on their resulting photoluminescent and radioluminescent properties. We further demonstrate the potential of these zinc tungstate nanorods for biomedical applications, such as photodynamic therapy for cancer treatment, by analyzing their toxicological profile within cell lines and neurons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Incident beam optics optimization for the single crystal neutron diffractometer Pioneer with a polarized beam option

Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Abstract This work presents the PORTALS framework (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no loss of accuracy. The efficiency of PORTALS is benchmarked against standard methods, and its full potential is demonstrated on a unique, simultaneous 5-channel (electron temperature, ion temperature, electron density, impurity density and angular rotation) prediction of steady-state profiles in a DIII-D ITER Similar Shape plasma with GPU-accelerated, nonlinear CGYRO (Candy et al 2016 J. Comput. Phys. 324 73–93). This paper also provides general guidelines for accurate performance predictions in burning plasmas and the impact of transport modeling in fusion pilot plants studies.

Physics↗
DOE OSTI2022

Considerations for a TeV collider based on dielectric laser accelerators

Particle acceleration in dielectric microstructures powered by infrared lasers, or "dielectric laser acceleration" (DLA), is a promising area of advanced accelerator research with the potential to enable more affordable and higher-gradient accelerators for energy frontier science and a variety of other applications. DLA leverages well-established industrial fabrication capabilities and the commercial availability of tabletop lasers to reduce cost, with axial accelerating fields in the GV/m range. Further, desirable luminosities would be obtained by operating with very low charge per bunch but at extremely high repetition rates. And as a consequence of its unique operating parameter regime, coupling of the laser to the accelerator can potentially be in the 50% range and with low beamstrahlung energy loss due at the interaction point, making DLA a promising approach for a future multi-TeV linear collider.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Deep decarbonization and U.S. biofuels production: a coordinated analysis with a detailed structural model and an integrated multisectoral model

Scenarios for deep decarbonization involve biomass for biofuels, biopower, and bioproducts, and they often include negative emissions via carbon capture and storage or utilization. However, critical questions remain about the feasibility of rapid growth to high levels of biomass utilization, given biomass and land availability as well as historical growth rates of the biofuel industry. We address these questions through a unique coordinated analysis and comparison of carbon pricing effects on biomass utilization growth in the United States using a multisectoral integrated assessment model, the Global Change Analysis Model (GCAM), and a biomass-to-biofuels system dynamics model, the Bioenergy Scenario Model (BSM). We harmonized and varied key factors—such as carbon prices, vehicle electrification, and arable land availability—in the two models. We varied the rate of biorefinery construction, the fungibility of feedstock types across conversion processes, and policy incentives in BSM. The rate of growth in biomass deployment under a carbon price in both models is within the range of current literature. However, the reallocation of land to biomass feedstocks would need to overcome bottlenecks to achieve growth consistent with deep decarbonization scenarios. Investments as a result of near-term policy incentives can develop technology and expand capacity—reducing costs, enabling flexibility in feedstock use, and improving stability—but if biomass demand is high, these investments might not overcome land reallocation bottlenecks. Biomass utilization for deep decarbonization relies on extraordinary growth in biomass availability and industrial capacity. In this paper, we quantify and describe the potential challenges of this rapid change.

09 BIOMASS FUELS↗
DOE OSTI2025

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from high-resolution imagery are an attractive option to reduce costs. To date, success with these methods has been demonstrated using multichannel aerial photography and specialized satellite data products derived from multiple sensors, neither of which is commonly available at temporal resolutions finer than one year. Here we demonstrate a method to generate sub-meter resolution CHMs in three forests in California using a more abundant data source: sub-meter resolution, panchromatic satellite imagery from a single sensor. We show that phenology and species composition play important roles in model transferability; when trained using imagery from a single conifer forest in autumn, the model performs well on autumn imagery from a second conifer forest several hundred kilometers distant with no re-training. With modest additions to the training dataset, the same model generates minimally biased estimates of canopy height in both conifer and deciduous forests during multiple seasons. Because the model operates on satellite data with global coverage and a relatively short return interval, we propose its suitability to extrapolate tree-level canopy height data to remote regions and conduct high-temporal resolution monitoring of forest structure. We furthermore demonstrate the workflow’s applicability to fire modeling by conducting simulations in forests populated by trees measured using both this approach and airborne lidar surveying. We find minimal differences in fire behavior relative to a baseline case in which only statistical distributions of tree height and crown area are known. This result underscores the value of forest structural information derived from our workflow for improving the fidelity of wildland fire simulations, among other ecological applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cheaper and more noise-resilient quantum state preparation using eigenvector continuation

Subspace methods are powerful, noise-resilient methods that can effectively prepare ground states on quantum computers. The challenge is to get a subspace with a small condition number that spans the states of interest using minimal quantum resources. In this work, we will use eigenvector continuation to build a subspace from the low-lying states of a set of Hamiltonians. The basis vectors are prepared using truncated versions of standard state preparation methods such as imaginary-time evolution (ITE), adiabatic state preparation (ASP), and variational quantum eigensolver. By using these truncated methods combined with eigenvector continuation, we can directly improve upon them, obtaining more accurate ground-state energies at a reduced cost. We use several spin systems to demonstrate convergence even when methods like ITE and ASP fail, such as ASP in the presence of level crossings and ITE with vanishing energy gaps. We also showcase the noise resilience of this approach beyond the gains already made by having shallower quantum circuits. Furthermore, our findings suggest that eigenvector continuation can be used to improve existing state preparation methods in the near term.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Two-way coupled particle-turbulence interaction: Effect of numerics and resolution on fluid and particle statistics

Euler-Lagrange point-particle simulation has emerged as a premier methodology for studying dispersed particle-laden flows. This method's popularity stems from its ability to resolve fine-scale fluid structures while also tracking individual particles at reduced cost using an appropriate particle acceleration model. However, the point-particle model has known convergence issues in that refinement of the fluid grid can lead to changes in the predicted statistics. The reasons for non-convergence are twofold: the point-particle two-way coupling force in the Navier-Stokes equations requires a numerical regularization and, without careful implementation, yields a singular force on the fluid with grid refinement. The second factor that yields grid-dependent statistics is that the point-particle force model in general depends on the undisturbed fluid velocity. When the undisturbed fluid velocity is not robustly modeled in a grid-insensitive way, the calculated force for both particles and fluid will be grid-dependent, contaminating their respective statistics. While the first issue regarding regularizing the point-particle source term has received attention in the literature, the consequences of robustly modeling the undisturbed velocity in the context of grid refinement of turbulence has received little attention. Here, we consider decaying homogeneous isotropic turbulence laden with particles at different Stokes numbers. For a given Stokes number, we systematically refine the grid and demonstrate that explicitly modeling the undisturbed fluid velocity yields relative grid insensitivity for the energy of the particle and fluid phases, as well as acceleration of the particles. We also demonstrate that an appropriately defined dissipation rate is also grid-insensitive when an undisturbed fluid velocity correction is used. In contrast, when the undisturbed fluid velocity is modeled using the conventional approach of interpolating the local fluid velocity to the particle location, we show this procedure yields divergent statistics with grid refinement. In particular, we show that higher-order interpolation of the fluid velocity in two-way coupled problems is worse than lower-order interpolation, in the absence of a correction procedure to estimate the undisturbed fluid velocity. We also examine velocity derivative statistics of the fluid phase and demonstrate that these statistics are not in general convergent even when the undisturbed fluid velocity is explicitly modeled. Collectively, the observations in this paper are used to present a philosophy on the types of questions which are answerable with point-particle methods.

42 ENGINEERING↗
DOE OSTI2020

A Novel AC to AC Wireless Power Transfer System for EV Charging Applications

In this paper, a novel ac to ac wireless power transfer (WPT) system is introduced for electric vehicle (EV) charging applications to reduce cost and design complexity. The presented wireless power transfer concept achieves unity power factor (UPF) on the grid-side by using a hybrid frequency ac / ac converter without an additional converter stage and closed loop control compared to the conventional systems. Due to inherent merit of the proposed ac / ac converter, ac input with 60 Hz grid frequency can be directly transferred to the load by superimposing with high frequency switching signal through the wireless coils. To validate the theoretical analysis of the proposed WPT system, the experimental results of the proposed converter are provided for 650 W output power by using 6 inches air gap between the couplers with the input of 110 VRMS ac source. The system overall efficiency is measured 89 % achieving 0.99 power factor (PF) and 1.5 % current total harmonic distortion (THD).

Asa, Erdem↗
DOE OSTI2022

Digital Twin of an ANPC inverter with integrated Design-For-Trust

Reducing costs and increasing manufacturing output while creating reliable products are three essential components needed to keep a business competitive. In the past, having an asset that could address these three challenges at the same time would be challenging. However, recent advances in computer processing capabilities coupled with increases to network speeds allowed such a system to become possible; and this is known as a Digital Twin (DT), which represents a virtual copy of a production system or a product. Here, this work exhibits a DT application of an Active Neutral Point Clamped (ANPC) inverter using a controller. The controller emulates the ANPC responses of a new Digital Signal Processing (DSP) firmware and validates this new firmware by using Design-For-Trust (DFTr) characteristics. If the new firmware is malicious, then it should be rejected, thus adding preemptive protection measures for inverter based distributed energy resources.

cybersecurity↗