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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Real-space Green’s function approach to photoelectron diffraction

We discuss the real-space Green’s function (RSGF) approach for core-level photoelectron diffraction (PD) and its comparison to x-ray absorption spectra (XAS). We focus especially on the separable Green’s function formalism for efficient calculations of high-order multiple scattering. Computational details such as scattering potentials, self-energy effects, Debye–Waller factors, and inelastic losses are discussed. Finally, we consider prospects for improving ab initio PD calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Chronology of ungrouped achondrites Northwest Africa 11119 and 7325/8486: implications for early evolution of a heterogeneous crust on a differentiated planetesimal

The chronology of ungrouped achondrites provides key insights into the timeline of igneous activity in the early Solar System. Two ungrouped achondrites – Northwest Africa (NWA) 11119 (andesite-dacite) and NWA 8486 and its pair NWA 7325 (olivine gabbro) – are the focus of this study, where their chronologies are investigated using multiple high-resolution techniques. Here we report the lead-lead (207Pb-206Pb) and manganese-chromium (53Mn-53Cr) systematics of NWA 11119, as well as the 207Pb-206Pb systematics of NWA 8486 alongside aluminum-magnesium (26Al-26Mg) systematics for NWA 7325. The U-corrected 207Pb-206Pb ages of NWA 11119 and the combined ages of NWA 7325/8486 are 4566.4 ± 0.8 Ma and 4563.8 ± 1.9 Ma, respectively. Additionally, we report the 53Mn-53Cr age of NWA 11119 to be 4564.4 ± 2.5 Ma and the 26Al-26Mg age of NWA 7325/8486 to be 4563.1 ± 0.3 Ma. The formation of NWA 11119 requires partial melting of a (likely chondritic) source reservoir leading to eruption of Si rich, alkali depleted magmas, while NWA 7325/8486 likely formed from a chemically fractionated reservoir with superchondritic Al/Mg. The clear geochemical and isotopic similarities of these achondrites, combined with the chronology reported here, is suggestive of formation of these two ungrouped achondrites on a common parent body which likely formed in the inner Solar System and experienced early differentiation under reducing conditions. If these achondrites did share a parent body, it would suggest that primary asteroids in the early Solar System commonly produced mineralogically and geochemically heterogeneous crusts. While mineralogical and geochemical heterogeneity is known to exist in the (mostly mafic) crust of asteroid Vesta, our findings show that even more significant crustal heterogeneity (representing felsic and mafic compositions) may exist on other asteroids.

Cartwright, Julia [University of Leicester, UK]↗
DOE OSTI2022

Structure of maize BZR1-type β-amylase BAM8 provides new insights into its noncatalytic adaptation

Plant β-amylase (BAM) proteins play an essential role in growth, development, stress response, and hormone regulation. Despite their typical (β/α) 8 barrel structure as active catalysts in starch breakdown, catalytically inactive BAMs are implicated in diverse yet elusive functions in plants. Further, the noncatalytic BAM7/8 contain N-terminal BZR1 domains and were shown to be involved in the regulation of brassinosteroid signaling and possibly serve as sensors of yet an uncharacterized metabolic signal. While the structures of several catalytically active BAMs have been reported, structural characterization of the catalytically inactive BZR1-type BAMs remain unknown. Here, we determine the crystal structure of β-amylase domain of Zea mays BAM8/BES1/BZR1-5 and provide comprehensive insights into its noncatalytic adaptation. Using structural-guided comparison combined with biochemical analysis and molecular dynamics simulations, we revealed conformational changes in multiple distinct highly conserved regions resulting in rearrangement of the binding pocket. Altogether, this study adds a new layer of understanding to starch breakdown mechanism and elucidates the acquired adjustments of noncatalytic BZR1-type BAMs as putative regulatory domains and/or metabolic sensors in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Process and feedstock driven microstructure for laser powder bed fusion of 316L stainless steel

Here in the pursuit of improving additively manufactured (AM) component quality and reliability, fine-tuning critical process parameters such as laser power and scan speed is a great first step toward limiting defect formation and optimizing the microstructure. However, the synergistic effects between these process parameters, layer thickness, and feedstock attributes (e.g. powder size distribution) on part characteristics such as microstructure, density, hardness, and surface roughness are not as well-studied. In this work, we investigate 316L stainless steel density cubes built via laser powder bed fusion (L-PBF), emphasizing the significant microstructural changes that occur due to altering the volumetric energy density (VED) via laser power, scan speed, and layer thickness changes, coupled with different starting powder size distributions. This study demonstrates that there is not one ideal process set and powder size distribution for each machine. Instead, there are several combinations or feedstock/process parameter ‘recipes’ to achieve similar goals. This study also establishes that for equivalent VEDs, changing powder size can significantly alter part density, GND density, and hardness. Through proper parameter and feedstock control, part attributes such as density, grain size, texture, dislocation density, hardness, and surface roughness can be customized, thereby creating multiple high-performance regions in the AM process space.

316L stainless steel↗
DOE OSTI2021

Efficient prediction of concentrating solar power plant productivity using data clustering

Concentrating solar power (CSP) plants convert solar energy to electricity and can be deployed with a thermal storage capability to shift electricity generation from time periods with available solar resource to those with high electricity demand or electricity price. Rigorous optimization of plant design and operational strategies can improve the market-competitiveness and commercial viability; however, such optimization may require hundreds of annual performance simulations, each of which can be computationally expensive when including considerations such as optimization of dispatch scheduling, sub-hourly time resolution, and stochastic effects due to uncertain weather or electricity price forecasts. This paper proposes a methodology to reduce the computational burden associated with simulation of electricity yield and revenue for CSP plants over a single- or multi-year period. Data-clustering techniques are employed to select a small number of limited-duration time blocks for simulation that, when appropriately weighted, can reproduce generation and revenue over a single year or within each year of a multi-year period. After selection of appropriate data features and weighting factors defining similarity between time-series profiles, the methodology captured annual revenue within 2.3%, 1.7%, or 1.2% using simulation of 10, 30, or 50 three-day exemplar time blocks, respectively, for each of three single-year location/weather/market scenarios and five plant configurations ranging from low to high solar multiple and storage capacity. When applied to multi-year datasets, the proposed methodology can capture inter-year variability that is unavailable from typical meteorological year (TMY) datasets while simultaneously requiring simulation of less than a single year of data.

14 SOLAR ENERGY↗
DOE OSTI2023

MOFX-DB: An Online Database of Computational Adsorption Data for Nanoporous Materials

Machine learning and data mining coupled with molecular modeling have become powerful tools for materials discovery. Metal-organic frameworks (MOFs) are a rich area for this due to their modular construction and numerous applications. Here, we make data from several previous large-scale studies in MOFs and zeolites from our groups (and new data for N 2 and Ar adsorption in MOFs) easily accessible in one place. The database includes over 3 million simulated adsorption data points for H 2 , CH 4 , CO 2 , Xe, Kr, Ar, and N 2 in over 160 000 MOFs and zeolites, textural properties like pore sizes and surface areas, and the structure file for each material. We include metadata about the Monte Carlo simulations to enable reproducibility. The database is searchable by MOF properties, and the data are stored in a standardized JSON format that that is interoperable with the NIST adsorption database. We also identify several MOFs that meet high performance targets for multiple applications, such as high storage capacity for both hydrogen and methane or high CO 2 capacity plus good Xe/Kr selectivity. Here, by providing this data publicly, we hope to facilitate machine learning studies on these materials, leading to new insights on adsorption in MOFs and zeolites.

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

The Many-Body Expansion for Metals: II. Nonadditive Terms in Clusters Composed of Metals with n s 1 , n s 2 , and n s 2 p 1 Configurations

The many-body expansion (MBE) was applied to homometallic and heterometallic trimers of metals with ns 1 , ns 2 , and ns 2 p 1 configurations to investigate its convergence, the magnitude and nature (stabilizing/destabilizing) of the individual terms and seek an understanding of their variation across the different families of clusters. In particular, we examined the series of alkali metals (Li 3 , Na 3 , K 3 , Li 2 Na, LiNa 2 ), alkali metal borides (Li 2 B and LiB 2 ), and alkaline earth metals (Be 3 , Be 2 Mg, BeMg 3 , and Mg 3 ) trimers, as well as sodium clusters Na n , n = 2–5. Here, we found that there is no uniform contribution (stabilizing or destabilizing) across the series in the different families of trimers. For instance, the 2-B term stabilizes the ground states of the Na 3 (doublet), Na 4 (singlet), and Na 5 (doublet) clusters, and the 3-B term destabilizes them; however, the opposite holds for the quartet state of the Li 3 , Li 2 Na, LiNa 2 , and Na 3 clusters (destabilizing 2-B, stabilizing 3-B). Substituting Li with B in the quartet state of Li 3 results in a significant reduction of the 3-B term amounting to 16% (Li 2 B) and 5% (LiB 3 ) of the binding energy. On the contrary, the ground states of the alkaline earth metal clusters (Be 3 , Be 2 Mg, BeMg 3 , and Mg 3 ) are stabilized by the 3-B term, while the 2-B term destabilizes them. Overall, we find that the 3-B terms significantly stabilize the high-spin multiplicity states of the ns 1 configurations and the low-spin states of the ns 2 configurations. Finally, as the size of the metal increases, the contribution of the 3-B term to the binding energy decreases due to the longer metal–metal bond distances.

Alkali metals↗
DOE OSTI2024

A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus Clouds Based on Three-Dimensional Path-Tracing

The complex spatial and temporal structure of cumulus clouds complicates their representation in weather and climate models. Classic meteorological instrumentation struggles to fully capture these features. Networks of multiple high-resolution hemispheric cameras are increasingly used to fill this data gap, and provide information on this missing multi-dimensional spatial information. In this study, a path-tracing algorithm is used to generate virtual camera images of resolved clouds in large-eddy simulations (LES). These images are then used as a camera network simulator, allowing reconstructions of three-dimensional cloud edges from the model output. Because the actual LES cloud field is fully known, the combined path-tracing and reconstruction method can be statistically analyzed. The method is applied to LES realizations of summertime shallow cumulus at the Jülich Observatory for Cloud Evolution (JOYCE), Germany, which also routinely operates a camera network. We find that the path-tracing method allows accurate reconstruction of up to 70% of the visible cloud edges. Additional sensitivity tests show that the method is robust for changes in its hyperparameters. The sensitivity to cloud optical thickness is also investigated, finding a cloud boundary placement error of approximately 182 m. This error can be considered typical for cloud boundary reconstruction using real stereo camera imagery. The results provide proof of principle for future use of the method for evaluating LES clouds against camera network imagery, and for further optimizing the configuration of such camera networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Microporous metal–organic frameworks for the purification of propylene

Separation of propylene from its analogous hydrocarbons such as propane is of great importance in the petrochemical industry to produce valuable chemical feedstocks with desired purity. However, the well-established method currently used for industrial propane/propylene separation is energy intensive. It involves repeated cycling in the cryogenic and high-pressure distillation process and requires multiple columns and high reflux ratios because of the very similar physical properties of the two species. Thus, it is identified as one of the most capital- and energy-intensive processes. Adsorptive separation based on porous adsorbents is regarded as an alternative energy-efficient technology to replace or supplement the traditional heat-driven cryogenic distillation processes. In this context, metal–organic frameworks (MOFs) have emerged as the most promising candidates for propane/propylene separation, taking into consideration their unique tunability with respect to pore geometry and pore functionality. In this highlight, we summarize the latest advancement in developing MOFs as physisorbents for the separation and purification of propylene from propane, with a focus on those that demonstrate selective molecular exclusion and propane-selective adsorption. We discuss the adsorption preferences related to the material design and separation mechanisms, and review the existing challenges. Lastly, we offer our perspectives on various strategies for the future design of MOFs that hold true potential for propylene purification under industrial settings.

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

Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence

Charged track reconstruction is a critical task in nuclear physics experiments, enabling the identification and analysis of particles produced in high-energy collisions. Machine learning (ML) has emerged as a powerful tool for this purpose, addressing the challenges posed by complex detector geometries, high event multiplicities, and noisy data. Traditional methods rely on pattern recognition algorithms like the Kalman filter, but ML techniques, such as neural networks, graph neural networks (GNNs), and recurrent neural networks (RNNs), offer improved accuracy and scalability. By learning from simulated and real detector data, ML models can identify and classify tracks, predict trajectories, and handle ambiguities caused by overlapping or missing hits. Moreover, ML-based approaches can process data in near-real-time, enhancing the efficiency of experiments at large-scale facilities like the Large Hadron Collider (LHC) and Jefferson Lab (JLAB). As detector technologies and computational resources evolve, ML-driven charged track reconstruction continues to push the boundaries of precision and discovery in nuclear physics. In these proceedings, we highlight advancements in charged track identification leveraging Artificial Intelligence within the CLAS12 detector, achieving a notable enhancement in experimental statistics compared to traditional methods. Additionally, we showcase real-time event reconstruction capabilities, including the inference of charged particle properties, such as momentum, direction, and species identification, at speeds matching data acquisition rates. These innovations enable the extraction of physics observables directly from the experiment in real-time.

Gavalian, Gagik (ORCID:0000000267385457)↗
DOE OSTI2020

Genome and time-of-day transcriptome of Wolffia australiana link morphological minimization with gene loss and less growth control

Rootless plants in the genus Wolffia are some of the fastest growing known plants on Earth. Wolffia have a reduced body plan, primarily multiplying through a budding type of asexual reproduction. Here, we generated draft reference genomes for Wolffia australiana (Benth.) Hartog & Plas, which has the smallest genome size in the genus at 357 Mb and has a reduced set of predicted protein-coding genes at about 15,000. Comparison between multiple high-quality draft genome sequences from W. australiana clones confirmed loss of several hundred genes that are highly conserved among flowering plants, including genes involved in root developmental and light signaling pathways. Wolffia has also lost most of the conserved nucleotide-binding leucine-rich repeat (NLR) genes that are known to be involved in innate immunity, as well as those involved in terpene biosynthesis, while having a significant overrepresentation of genes in the sphingolipid pathways that may signify an alternative defense system. Diurnal expression analysis revealed that only 13% of Wolffia genes are expressed in a time-of-day (TOD) fashion, which is less than the typical ~40% found in several model plants under the same condition. In contrast to the model plants Arabidopsis and rice, many of the pathways associated with multicellular and developmental processes are not under TOD control in W. australiana, where genes that cycle the conditions tested predominantly have carbon processing and chloroplast-related functions. The Wolffia genome and TOD expression data set thus provide insight into the interplay between a streamlined plant body plan and optimized growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structure of even-even Sr isotopes with 50 ≤ N ≤ 58 neutrons

Excited levels in Sr 90 , Sr 92 , Sr 94 , and Sr 96 nuclei were reinvestigated using high-statistics multiple- γ coincidence data from neutron-induced fission of U 235 and spontaneous fission of Cf 252 , measured using Exogam at Institut Laue Langevin and Gammasphere arrays, respectively. The experimental goal was the search for new excited levels and firm spin-parity assignments to known levels. A total of 23 new levels with 30 new or corrected decays and 39 new or improved spin-parity assignments were obtained in the four nuclei. Negative-parity structures on top of 3 - excitation were firmly identified and extended to higher spins. New positive-parity structures in Sr 94 and Sr 96 were observed with 3 + excitations characteristic of γ collectivity. The 277.7-keV, E 2 decay from the 1507.0-keV level to the second 0 + level in Sr 96 , found in this paper, completes the coexisting deformed band in this nucleus. To learn about the microscopic structure of levels in the Sr 88 - 96 nuclei, we performed large-scale shell-model calculations. The calculations compared to the experiment, helped the discussion of the evolution of collectivity in strontium isotopes, highlighting the important role of various single-particle excitations in phase transitions and shape coexistence in the region. The special role of the neutron 9 / 2 + [ 404 ] extruder as a catalyst of the deformation change in the region is highlighted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Privacy-Preserving Federated Learning for Science: Challenges and Research Directions

This paper discusses the key challenges and future research directions for privacy-preserving federated learning (PPFL), with a focus on its application to large-scale scientific AI models, in particular, foundation models~(FMs). PPFL enables collaborative model training across distributed datasets while preserving privacy-- an important collaborative approach for science. We discuss the need for efficient and scalable algorithms to address the increasing complexity of FMs, particularly when dealing with heterogeneous clients. In addition, we underscore the need for developing advance privacy-preserving techniques, such as differential privacy, to balance privacy and utility in large FMs emphasizing fairness and incentive mechanisms to ensure equitable participation among heterogeneous clients. Finally, we emphasize the need for a robust software stack supporting scalable and secure PPFL deployments across multiple high-performance computing facilities. We envision that PPFL would play a crucial role to advance scientific discovery and enable large-scale, privacy-aware collaborations across science domains.

Kim, Kibaek [Argonne National Laboratory (ANL)]↗
DOE OSTI2024

A Large-Scale Analysis to Optimize the Control and V2V Communication Protocols for CDA Agreement-Seeking Cooperation

Cooperative driving automation (CDA) Class C, agreement-seeking cooperation, is an innovative and practical solution that can promote cooperation among general passenger vehicles on the road. However, more comprehensive studies are needed before establishing the standard protocols of agreement-seeking cooperation, such as communication frequency and the duration of cooperation. Here, this article presents an initiative study on the impacts of communication capabilities on agreement-seeking cooperation. Through a large-scale analysis by regulating vehicle-to-vehicle (V2V) communication metrics, this work suggests desirable system parameters that can maximize the benefits of cooperation and ensure reliable operability while avoiding exhaustive communication loads. As the first step, an example agreement-seeking cooperation system is created for a car-following scenario, including decision-making and control algorithms for autonomous vehicles. Then, software-in-the-loop tests explore the performance of the developed system as it encounters various communication risks, such as latency and message packet drops. The system performance metrics are evaluated from various angles, including the time consumed for the agreement-seeking process, cooperation ratio, and the ratio of faulty cooperation. Energy saving from the cooperation is assessed by using simulation software that can run multiple high-fidelity vehicle models simultaneously. Based on the analyses, this article suggests the V2V communication requirements for the reliable operation of CDA agreement-seeking, which can be referred to when developing the standard protocols of agreement-seeking cooperation.

42 ENGINEERING↗
DOE OSTI2021

Diverse Super-Resolution (diversity_SR) [SWR-21-60]

Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.

Glaws, Andrew↗
DOE OSTI2025

Data for Redefining the Product Portfolio of Oilcane Bagasse Biorefinery: Recovering Natural Colorants, Vegetative Lipids and Sugars

:Bioenergy crops have been known for their ability to produce biofuels and bioproducts. In this study, the product portfolio of recently developed transgenic sugarcane (oilcane) bagasse has been redefined for recovering natural pigments (anthocyanins), sugars, and vegetative lipids. The total anthocyanin content in oilcane bagasse has been estimated as 92.9 ± 18.9 µg/g of dried bagasse with cyanidin-3-glucoside (13.5 ± 18.9 µg per g of dried bagasse) as the most prominent anthocyanin present. More than 85 % (w/w) of the total anthocyanins were recovered from oilcane bagasse at a pretreatment temperature of 150 °C for 15 min. These conditions for the hydrothermal pretreatment also led to a 2-fold increase in the glucose yield upon the enzymatic saccharification of the pretreated bagasse. Further, a 1.5-fold enrichment of the vegetative lipids was demonstrated in the pretreated residue. Re-defining green biorefineries with multiple high-value products in a zero-waste approach is the need of the hour for attaining sustainability.

Biomass Analytics↗