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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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unraveling Hydrogen Induced Geochemical Reaction Mechanisms through Coupled Geochemical Modeling and Machine Learning

Underground hydrogen storage (UHS) provides a promising large-scale, long-term energy storage solution. A reasonable recovery of stored hydrogen is critical for a successful storage scheme. However, in subsurface reservoirs hydrogen is subject to active geochemical reactions that might result in hydrogen loss. In this study, we implemented a geochemical modeling approach coupled with an unsupervised machine learning technique called non-negative matrix factorization (NMF) to unravel the complex brine-rock-H 2 geochemical processes responsible for hydrogen losses, with particular focus on sulfate reduction reactions. NMF is applied to modeled mineral evolution and fluid component profiles to retrieve profiles that can be interpreted to more easily assess competing processes. NMF decouples simulated competing equilibrium reactions. This facilitates separation of overlapping reaction profiles from redox processes, dissolution fronts, and secondary precipitation while considering the effects of simulation parameters such as salinity, temperature, and total H 2 pressure. NMF successfully discriminates these competing effects in nonlinear ways, allowing robust interpretation. In addition, NMF reveals subtle coupled mineral associations and reaction fronts that are invisible to conventional model analysis. This integrated approach strengthens the conceptual understanding of complex nonlinear hydrogen-brine-rock interactions and advances geochemical research on UHS systems to resolve complexities in modeled geochemical systems without the need for direct experiments or prior knowledge. Furthermore, this study highlights the efficacy of combining geochemical modeling with machine learning techniques to enhance the interpretability of the intricate geochemical simulation output through deciphering the overlapping reaction path that cannot be achieved only using conventional analysis of geochemical models alone.

08 HYDROGEN↗
DOE OSTI2025

Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions

Predicting the binding affinity of ligands to protein pockets is key in the drug design pipeline. The flexibility of ligand-pocket motifs arises from a range of attractive and repulsive electronic interactions during binding. Accurately accounting for all interactions requires robust quantum-mechanical (QM) benchmarks, which are scarce for ligand-pocket systems. Additionally, disagreement between “gold standard” Coupled Cluster (CC) and Quantum Monte Carlo (QMC) methods casts doubt on many benchmarks for larger non-covalent systems. We introduce the “QUantum Interacting Dimer” (QUID) benchmark framework containing 170 non-covalent (non-)equilibrium systems modeling chemically and structurally diverse ligand-pocket motifs. Symmetry-adapted perturbation theory shows that QUID broadly covers non-covalent binding motifs and energetic contributions. Robust binding energies are obtained using complementary CC and QMC methods, achieving agreement of 0.5 kcal/mol. The benchmark data analysis reveals that several dispersion-inclusive density functional approximations provide accurate energy predictions, though their atomic van der Waals forces differ in magnitude and orientation. Contrarily, semiempirical methods and empirical force fields require improvements in capturing non-covalent interactions (NCIs) for out-of-equilibrium geometries. The wide span of NCIs, highly accurate interaction energies, and analysis of molecular properties take QUID beyond the “gold standard” for QM benchmarks of ligand-protein systems.

Puleva, Mirela [University of Luxembourg, Luxembou↗
DOE OSTI2024

Two-dimensional-lattice-confined single-molecule-like aggregates

Intermolecular distance largely determines the optoelectronic properties of organic matter. Conventional organic luminescent molecules are commonly used either as aggregates or as single molecules that are diluted in a foreigner matrix. They have garnered great research interest in recent decades for a variety of applications, including light-emitting diodes, lasers and quantum technologies, among others. However, there is still a knowledge gap on how these molecules behave between the aggregation and dilution states. Here we report an unprecedented phase of molecular aggregate that forms in a two-dimensional hybrid perovskite superlattice with a near-equilibrium distance, which we refer to as a single-molecule-like aggregate (SMA). By implementing two-dimensional superlattices, the organic emitters are held in proximity, but, surprisingly, remain electronically isolated, thereby resulting in a near-unity photoluminescence quantum yield, akin to that of single molecules. Moreover, the emitters within the perovskite superlattices demonstrate strong alignment and dense packing resembling aggregates, allowing for the observation of robust directional emission, substantially enhanced radiative recombination and efficient lasing. Molecular dynamics simulations together with single-crystal structure analysis emphasize the critical role of the internal rotational and vibrational degrees of freedom of the molecules in the two-dimensional lattice for creating the exclusive SMA phase. Furthermore, this two-dimensional superlattice unifies the paradoxical properties of single molecules and aggregates, thus offering exciting possibilities for advanced spectroscopic and photonic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Molecular dynamics simulation of radiation damage cascades in diamond

Radiation damage cascades in diamond are studied by molecular dynamics simulations employing the Environment Dependent Interaction Potential for carbon. Primary knock-on atom (PKA) energies up to 2.5 keV are considered and a uniformly distributed set of 25 initial PKA directions provide robust statistics. The simulations reveal the atomistic origins of radiation-resistance in diamond and provide a comprehensive computational analysis of cascade evolution and dynamics. As for the case of graphite, the atomic trajectories are found to have a fractal-like character, thermal spikes are absent and only isolated point defects are generated. Quantitative analysis shows that the instantaneous maximum kinetic energy decays exponentially with time, and that the timescale of the ballistic phase has a power-law dependence on PKA energy. Defect recombination is efficient and independent of PKA energy, with only 50% of displacements resulting in defects, superior to graphite where the same quantity is nearly 75%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Ohmic contacts to nitrogen-incorporated n-type ultrananocrystalline diamond film grown on intrinsic single crystal diamond substrate

Nitrogen-incorporated ultrananocrystalline diamond (n-UNCD) films offer tremendous potential for diverse electronic applications. However, the absence of a reliable Ohmic contact at room temperature limits their practical integration and broader applicability. Here, in this study, we investigate the room temperature specific contact resistivity (ρ c ) of Ti/Pt/Au metal stack deposited on n-UNCD films grown on an intrinsic single crystal diamond substrate using a microwave plasma chemical vapor deposition system. We employ a circular transfer length model (c-TLM) and find the room temperature ρ c to be ∼4.67 × 10 −5 Ω cm 2 , which is among the lowest reported value for n-UNCD films. High temperature vacuum annealing conducted at 700 and 800 °C results in an initial improvement, followed by a minor degradation in ρ c values, respectively. The electrical contacts remain highly Ohmic for all measurements. Furthermore, cross-sectional transmission electron microscopy analysis suggests formation of conductive titanium carbide layer with no significant inter metallic diffusion. Overall, the electrical contacts demonstrate robust thermal stability, both of which are critical for attaining high-performance nanocrystalline diamond-based electronic devices.

Low resistance contacts↗
DOE OSTI2015

Three super-earths orbiting HD 7924

We report the discovery of two super-Earth-mass planets orbiting the nearby K0.5 dwarf HD 7924, which was previously known to host one small planet. The new companions have masses of 7.9 and 6.4 M{sub ⊕}, and orbital periods of 15.3 and 24.5 days. We perform a joint analysis of high-precision radial velocity data from Keck/HIRES and the new Automated Planet Finder Telescope (APF) to robustly detect three total planets in the system. We refine the ephemeris of the previously known planet using 5 yr of new Keck data and high-cadence observations over the last 1.3 yr with the APF. With this new ephemeris, we show that a previous transit search for the inner-most planet would have covered 70% of the predicted ingress or egress times. Photometric data collected over the last eight years using the Automated Photometric Telescope shows no evidence for transits of any of the planets, which would be detectable if the planets transit and their compositions are hydrogen-dominated. We detect a long-period signal that we interpret as the stellar magnetic activity cycle since it is strongly correlated with the Ca ii H and K activity index. We also detect two additional short-period signals that we attribute to rotationally modulated starspots and a one-month alias. The high-cadence APF data help to distinguish between the true orbital periods and aliases caused by the window function of the Keck data. The planets orbiting HD 7924 are a local example of the compact, multi-planet systems that the Kepler Mission found in great abundance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Tree-based algorithms for weakly supervised anomaly detection

Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable performance on specific signatures such as dijet resonances, their application in a more model-agnostic manner requires dealing with a larger number of potentially noisy input features. In this paper, we show that using boosted decision trees as classifiers in weakly supervised anomaly detection gives superior performance compared to deep neural networks. Boosted decision trees are well known for their effectiveness in tabular data analysis. Our results show that they not only offer significantly faster training and evaluation times, but they are also robust to a large number of noisy input features. By using advanced gradient boosted decision trees in combination with ensembling techniques and an extended set of features, we significantly improve the performance of weakly supervised methods for anomaly detection at the LHC. This advance is a crucial step toward a more model-agnostic search for new physics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2026

Submodule-Level Decentralized Control for Cascaded Quadruple Active Bridge-Based Medium-Voltage Converters

High-power, low-voltage DC (LVDC) loads, such as AI data centers, electric vehicle fast-charging hubs, and hydrogen electrolyzers, are accelerating the deployment of solid-state transformers (SSTs) that directly interface medium-voltage AC (MVAC) to LVDC, streamlining power delivery. This paper proposes a submodule-level decentralized control strategy for an SST comprising a cascaded H-bridge (CHB) active rectifier on the MVAC side and per-module quadruple-active-bridge (QAB) converters on the LVDC side with local controllers. The proposed strategy eliminates the need for high-fidelity, real-time cross-isolation communication by synchronizing all active bridges to a common heartbeat signal and enabling the primary- and secondary-side controllers to generate independent local control signals (phase shifts). The resultant phase shifts naturally govern average and double-line frequency power transfer between active bridges, enabling each side to meet its control objectives using only local measurements. Detailed controller design considerations are presented based on a stability analysis. Comprehensive electromagnetic-transient simulations demonstrate tight DC-link voltage regulation, high-quality grid currents, and robust operation under load transients and grid disturbances, without real-time communication among the submodule controllers. These results indicate that the proposed scheme can significantly enhance the reliability, scalability, and flexibility of cascaded bridge-based medium-voltage converters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing

Abstract We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0–5‐log 10 reduction in Salmonella ) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400 – 248,000) cases/year. Risk reduction (by 5 ‐ to 7‐fold) predicted from a 1‐log 10 seed treatment alone was comparable to SIW testing alone, and each additional 1‐log 10 seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3‐log 10 or a 5‐log 10 seed treatment reduced the predicted cases/year to 139 (95% CI 33 – 448) or 1.4 (95% CI <1 – 4.5), respectively. Combined with SIW testing, a 3‐log 10 or 5‐log 10 seed treatment reduced the cases/year to 45 (95% CI 10–146) or <1 (95% CI <1 – 1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3‐log 10 seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22 – 298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Secondary ion mass spectrometry for superconducting radiofrequency cavity materials

Historically, many advances in superconducting radio frequency (SRF) cavities destined for use in advanced particle accelerators have come empirically, through the iterative procedure of modifying processing and then performance testing. However, material structure is directly responsible for performance. Understanding, the link between processing, structure, and performance will streamline and accelerate the research process. In order to connect processing, structure, and performance, accurate and robust materials characterization methods are needed. Here in this paper, one such method, SIMS, is discussed with focus on analysis of SRF materials. In addition, several examples are presented, showing how SIMS is being used to further understanding of materials based SRF technologies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

SU-F-BRD-02: Incorporating Uncertainty Analysis in Plan Comparison of VMAT, Double Scattering Proton Plan and IMPT for Lung Irradiation

Purpose: We investigate the effect of residual setup and motion errors in lung irradiation for VMAT, double scattering (DS) proton beams and spot scanning (IMPT) in a case study. Methods: The CT image and contour sets of a lung patient treated with 6 MV VMAT is re-planned with DS as well as IMPT subject to the same constraints; V20(lung), V10(lung) and V5(lung)< 15%, 20% and 25% respectively, V20(heart)<25% and V100%(PTV)≥95%. In addition, uncertainty analysis in the form of isocenter shifts (±1–3mm) was incorporated in the DVH calculations to assess the plan robustness. Results: Only the IMPT plan satisfies all the specified constraints. The 3D-conformal DS proton plan is able to achieve better sparing of the lung and heart dose compared to VMAT. For the lung, V20, V10 and V5 are 13%, 19% and 25% respectively for IMPT, 18%, 23% and 30% respectively for DS, and 20%, 30% and 42% respectively for VMAT. For heart: 0.6% for IMPT, 2.4% for DS and 30% for VMAT. When incorporating isocenter shifts in DVH calculations, the maximum changes in V20, V10 and V5 for lung are 14%, 21% and 28% respectively for IMPT. The corresponding max changes are19%, 24% and 32% respectively for DS, and 22%, 32% and 44% respectively for VMAT. The largest change occurs in the PTV coverage. For IMPT, V100%(PTV) varies between 88–96%, while V100%(PTV) for VMAT suffers a larger change compared to DS (Δ=5.5% vs 3.3%). Conclusion: While only IMPT satisfies the stringent dose-volume constraints for the lung irradiation, it is not as robust as the 3D conformal DS plan. DS also has better sparing in lung and heart compared to VMAT and similar PTV coverage. By including isocenter shifts in dose-volume calculations in treatment planning of lung, DS appears to be more robust than VMAT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Master of Puppets: Cooperative Multitasking for In Situ Processing

Modern scientific and engineering simulations track the time evolution of billions of elements. For such large runs, storing most time steps for later analysis is not a viable strategy. It is far more efficient to analyze the simulation data while it is still in memory. Here, we present a novel design for running multiple codes in situ: using coroutines and position-independent executables we enable cooperative multitasking between simulation and analysis, allowing the same executables to post-process simulation output, as well as to process it on the fly, both in situ and in transit. We present Henson, an implementation of our design, and illustrate its versatility by tackling analysis tasks with different computational requirements. This design differs significantly from the existing frameworks and offers an efficient and robust approach to integrating multiple codes on modern supercomputers. The techniques we present can also be integrated into other in situ frameworks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Henson v1.0

Modern scientific and engineering simulations track the time evolution of billions of elements. For such large runs, storing most time steps for later analysis is not a viable strategy. It is far more efficient to analyze the simulation data while it is still in memory. The developers present a novel design for running multiple codes in situ: using coroutines and position-independent executables they enable cooperative multitasking between simulation and analysis, allowing the same executables to post-process simulation output, as well as to process it on the fly, both in situ and in transit. They present Henson, an implementation of our design, and illustrate its versatility by tackling analysis tasks with different computational requirements. Our design differs significantly from the existing frameworks and offers an efficient and robust approach to integrating multiple codes on modern supercomputers. The presented techniques can also be integrated into other in situ frameworks.

Monozov, Dmitriy↗
DOE OSTI2024

raogroupuiuc/yl_variantcalling

NGS analysis for mutation analysis in Yarrowia lipolytica evolved strains. Yarrowia lipolytica, an oleaginous yeast, shows promise for industrial fermentation due to its robust acetyl-CoA flux and well-developed genetic engineering tools. However, its lack of an active xylose metabolism restricts the conversion of cellulosic sugars to valuable products. To address this, metabolic engineering, and adaptive laboratory evolution (ALE) were applied to the Y. lipolytica PO1f strain, resulting in an efficient xylose-assimilating strain (XEV). Whole-genome sequencing (WGS) of the XEV followed by reverse engineering revealed that the amplification of the heterologous oxidoreductase pathway and a mutation in the GTPase-activating protein gene (YALI0B12100g) might be the primary reasons for improved xylose assimilation in the XEV strain. When a sorghum hydrolysate was used, the XEV strain showed superior xylose consumption and lipid production compared to its parental strain (X123). This study advances our understanding of xylose metabolism in Y. lipolytica and proposes effective metabolic engineering strategies for optimizing lignocellulosic hydrolysates.

Deewan, Anshu↗
DOE OSTI2019

Nuclear Data – Benchmarking 19 F(α,n) Yield Data for Nuclear Safeguards

Fluorine compounds of U and Pu are ubiquitous in the nuclear fuel cycle, so F(α,n) neutrons are an important signature and quantitative source term that needs to be understood for physics-based interpretation of nondestructive assay measurements. Historically there have been large differences in the basic nuclear data for this reaction reported by various groups. UF 6 is the most prominent material in the nuclear fuel cycle, with the potential for short-term production into weaponizable form. Verification of bulk quantities, natural feed, depleted tails, and especially low enriched product in cylinders is particularly important. The principal physical measurement is neutron counting. For enriched material, the 19 F(α,n) reaction, driven by 234U, is the dominant source of neutrons. Basic nuclear data, cross sections, needed to calculate the yield, as well as information on the source spectrum for sensitivity studies are sparse and highly discrepant. This limits defensible physics-based performance evaluations. The same applies to holdup and criticality studies in which hydrated uranyl fluoride is the material of interest which accumulates in enrichment facilities. In the future we anticipate that the physics community will have made improved accelerator-based measurements and undertaken a more thorough evaluation and adjustment of all relevant available data. But in the short term, this does not help the safeguards community face the pressing real-world nondestructive assay requirements. To address this need, we have performed quality neutron measurements on UF6 materials using well-known material and high-capability neutron counters. A robust determination of the n/s/g of 234 U in UF 6 was generated along with a scientifically defensible uncertainty analysis. The weighted average value of the neutron yield is 509 n/s/g 234 U with a random uncertainty of approximately 1%. Dominant sources of systematic uncertainty are in the efficiency determination where we incur approximately 1.1% relative standard deviation associated with the 252 Cf reference source and about 0.9% uncertainty coming from the uncertainty in the F(α,n) spectrum. The stated uncertainties are an order of magnitude better than current data based on accelerator data reported in the literature. Aside from being of immediate and direct use by the safeguards community, this result will serve as an enduring integral benchmark for subsequent data evaluations that will need to match it in order to be credible. In addition to yield normalization, safeguards users of F(α,n) data also need guidance of the neutron emission spectrum. We have generated a neutron emission using a modified version of the well-known SOURCES 4C code, updated with new alpha stopping power coefficients, and a blended microscopic cross section data set. The yield and spectra are available in a form that MCNP users can readily use.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Combustion Research I.1 Sprays, Flow, Heat Transfer and Turbulent Mixing

LANL is working with the Partnership for Advance Combustion Engines (PACE) a DOE sponsored consortium of national laboratories for the research and development for creating smarter engine design tools for sustainable transportation. Much of that effort is focused on heat, mass and momentum transfer within and engine. LANL’s focus in 2019, in particular under PACE has been spray modeling and engine mixture formulation, development of conjugate heat transfer analysis (heat transfer to the environment surrounding the combustion chamber). Our efforts relay on the Fast, Easy, Accurate and Robust Continuum Engineering (FEARCE) software developed at LANL as the next generation of engine modeling software for turbulent reactive and multiphase flow, a 2019 R&D 100 winner. This work is relevant to the DOE Vehicle Technologies Office efforts at addressing national energy security as well. Less dependence on petroleum products leads to greater energy security. By Environmental Protection Agency standards, some vehicles are now reaching 42–50 mpg mark. These are conventional gasoline engines. With continued investment and research into new technical innovations, the potential exists to save more than 4 million barrels of oil per day or approximately $200 to $400 million per day. This would be a significant decrease in emissions and use of petroleum and a very large stimulus to the U.S. economy. Better understanding of fuel injection and fuel–air mixing, thermodynamic combustion losses, and combustion/emission formation processes enhances our ability to minimize fuel use and unwanted emissions. Helping to accomplish this understanding, the FEARCE modeling program is working to provide state-of-theart capability for accurately simulating combustion processes: to have a predictive methodology in a software helping industry and researchers not only meet national goals on fuel usage and emissions, but global goals. In addition, a predictive, robust, and accurate capability for simulating the engine combustion process helps to minimize time and labor for development of new engine technology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

97 MATHEMATICS AND COMPUTING↗

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