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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nanostructure and compositional segregation of soft magnetic FeNi-based nanocomposites with multiple nanocrystalline phases

Soft magnetic metal amorphous nanocomposite alloys are produced through rapid solidification and thermal annealing yielding nanocrystals embedded within an amorphous precursor. Similar free energies in Co-rich and FeNi-based alloy systems result in multiple nanocrystalline phases being formed during devitrification. Studies of multi-phase crystallization processes have been reported for Co-rich alloys but relatively few have investigated FeNi-based systems. A detailed characterization of compositional partitioning and microstructure of an optimally annealed FeNi-based MANC (Fe 70 Ni 30 ) 80 Nb 4 Si 2 B 14 alloy is presented through complementary high-resolution transmission electron microscopy (HRTEM) and atom probe tomography (APT). HRTEM demonstrates orientation relationships between FCC and BCC nanocrystals, suggesting heterogeneous nucleation of nanocrystals in the amorphous matrix or a cooperative mechanism of nucleation between BCC and FCC nanocrystallites. APT results show evidence for (i) the segregation of Fe and Ni between nanocrystals of different phases, (ii) B partitioning to the amorphous phase, and (iii) an Nb-enriched shell surrounding nanocrystals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cesium-Technetium Volatility in the DFLAW Flow-Sheet (VSL-21R4780-1 Rev. 0)

The tests were conducted on the DM10 vitrification system with prototypical off-gas treatment system, which includes an SBS and WESP. This allowed determination of the partitioning and speciation of cesium between the melter and the off-gas system components, including liquid effluents from the SBS and WESP. The tests were conducted using simulated Hanford LAW AP-107, which is the planned first feed to DFLAW, at a nominal feed concentration of 5.6 molar Na over about 200 hours of testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗
DOE OSTI2022

Implications of Underground Nuclear Explosion Cavity Evolution for Radioxenon Isotopic Composition

Abstract Isotopic ratios of radioxenons sampled in the atmosphere or subsurface can be used to verify the occurrence of an underground nuclear explosion (UNE). Differences in the half-lives of radioactive xenon precursors and their decay-chain networks produce different time-dependent concentration profiles of xenon isotopes allowing isotopic ratios to be used for tracking UNE histories including estimating the time of detonation. In this study, we explore the potential effects of post-detonation cavity processes: precipitation of iodine precursors, gas seepage, and prompt venting on radioxenon isotopic evolution which influences UNE histories. Simplified analytical models and closed-form solutions yielding a potentially idealized radioactive decay/ingrowth chain in a closed and well-mixed system typically have limited application by not including the partitioning of the radionuclide inventory between a gas phase and rock melt created by the detonation and by ignoring gas transport from the cavity to host rock or ground surface. In reality, either subsurface transport or prompt release that is principally responsible for gas signatures violates the closed-system (or batch-mode) assumption. A closed-form solution representing time-dependent source-term activities is extended by considering the cavity partitioning process, slow seepage, and/or prompt release of gases from the cavity and applied to realistic systems.

Sun, Yunwei (ORCID:0000000194801439)↗
DOE OSTI2024

Anion Selectivities in Zwitterion Grafted Nanopores: Effect of Zwitterion Architecture

The separation of ions of similar charge is a crucial challenge in many applications, from water treatment to precious metal recovery. Membranes with cross-linked zwitterionic amphiphilic copolymer (ZAC-X) selective layers, which feature self-assembled, zwitterion-lined nanodomains for permeation, offer unique permselectivity between monovalent anions (e.g. $\mathrm{Cl^-}$/$\mathrm{F^-}$). This has motivated studies on the mechanisms of transport and selectivity in this family of materials. In this study, we conducted molecular dynamics simulations of aqueous salt solutions within zwitterion-functionalized nanopores to elucidate the influence of dipole orientation of the ZI ligands on anion diffusivities, partitioning, and permeabilities. Here, our model compares systems with contrasting ZI organization: surface-cation-anion ($\mathrm{S\text{-}ZI^{+}\text{-}ZI^{-}}$, Motif A) and surface-anion-cation ($\mathrm{S\text{-}ZI^{-}\text{-}ZI^{+}}$, Motif B). Our results reveal that Motif A exhibits less pronounced ion pairing due to a spatial separation in the radial profiles of cations and anions. Motif B demonstrates prominent ion pairing for smaller anions owing to their overlap with cation distributions. Further, our potential of mean force profiles reveal that anion partitioning increases with anion size in both ligand motifs, whereas Motif B exhibits significantly higher partitioning selectivity towards larger anions compared to Motif A. Our results for ion diffusivities show that the self-diffusivities of both anions and cations are lower for Motif B compared to Motif A. Such trends in anion partitioning and diffusivities can be explained by differences in the interactions and steric hindrance experienced by the anionic species in Motifs A and B. Finally, our results for anion permselectivity, obtained by combining partitioning and diffusivity, indicate that partitioning trends dominate over diffusivity trends. Consequently, anion permeability increases with anion size, and ligand Motif B yields much higher permselectivity towards larger anions compared to ligand Motif A.

anions↗
DOE OSTI2026

Chemical Recommender System: Replacement Suggestions for Small Molecules

The Chemical Recommender System (CRS) is an open-source, high-performance toolkit that enables real-time similarity searches across the complete PubChem database (over 50 million molecules) using commodity hardware. The CRS addresses critical limitations in existing chemical informatics platforms through a novel vector database infrastructure, extensible model integration capabilities, and complete algorithmic transparency. The system implements a vector database deployment with partitioned indexing that achieves a ~60x speedup over traditional approaches. A containerized model integration framework allows researchers to seamlessly incorporate custom predictive models into the full-scale search and scoring pipeline, while complete configurability of search parameters, filtering logic, and scoring functions provides capabilities not available in existing black-box solutions. Beyond structural similarity, the CRS integrates OPERA QSAR models for thermophysical and toxicity predictions, RDKit synthetic accessibility scoring, and user-defined models to compute weighted final replacement scores. The complete system is accessible through an interactive web application supporting real-time progress monitoring, post-processing score re-weighting, automated PDF reporting, and batch processing capabilities.

Nair, Parthiv Anand [Sandia National Laboratories ↗
DOE OSTI2025

Adsorption and Chromatographic Behavior of Dispersed Sodium Bismuthate Systems for the Separation of Americium from Curium

The selective partitioning of americium (Am) and curium (Cm) is integral for nuclear science areas such as the nuclear fuel cycle, stockpile stewardship, and isotope production but remains a long-standing radioanalytical challenge due to nearly identical chemical properties. Differences in redox chemistry can be exploited since Am can be oxidized to the hexavalent oxidation state. Sodium bismuthate (NaBiO 3 ) exhibits favorable oxidation and ion exchange characteristics conducive to a rapid and efficient Am/Cm chromatographic separation. Contact of nitric acid with NaBiO 3 was shown to significantly decrease the nitric acid concentration and solution volume. The adsorption, kinetic, and chromatographic behavior of Am and Cm in systems that disperse NaBiO3 in filter aids was evaluated. Further, dispersion of NaBiO 3 increased separation factors to over 100, with rapid kinetics achieved within 1 min of contact and sustained for at least 2 h. The adsorption capacity was more than doubled from 0.066 mequiv g –1 for solid NaBiO 3 alone to 0.149(6) and 0.156(9) meq g –1 when dispersed in Celite 545 and silica gel, respectively. Complete separation was achieved in all systems with ~100% recovery in the respective eluted fractions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

PUMIPic: A mesh-based approach to unstructured mesh Particle-In-Cell on GPUs

Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. Here, this paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Distribution of Infiltration in the 216-U-10, 216-B-3 Pond, and 216-T-4 Pond Systems 1944-1997

A modeling system to simulate fate and transport of contaminant plumes in groundwater beneath the Central Plateau to support the Cumulative Impact Evaluation (CIE) and Composite Analysis (CA) is being developed. The CIE will evaluate the cumulative effect of multiple Central Plateau radiological and chemical sources on groundwater quality. This will enable cleanup decisions to be evaluated in the context of all Central Plateau waste sites and existing groundwater conditions. The purpose of this Environmental Calculation File (ECF) is to partition the infiltration of wastewater and contaminant inventory between the main pond and each expansion lobe of the 216-B-3 Pond system, and to partition the infiltration of wastewater and contaminant inventory between the ditches and ponds of the 216-U-10 Pond and 216-T-4 Pond systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Influences on Discharge Partitioning on a Large River Delta: Case Study of the Mississippi-Atchafalaya Diversion, 1926-1950

The modern Mississippi River (M.R.) Delta is plumbed by the Mississippi and Atchafalaya rivers, setting water and sediment dispersal pathways for Earth’s fifth-largest river system. The Atchafalaya River’s (A.R.) partial annexation of discharge from the M.R., particularly between 1926 and 1950, prompted warnings of a rapid river avulsion and the construction of the Old River Control Structure to regulate flow. Natural and anthropogenic causes of this discharge annexation are difficult to disentangle. Here, we develop and validate a hydrodynamic model of flow partitioning through the historic channel network. We then isolate how several key changes to the system affected discharge partitioning and stage at the A.R.-M.R. diversion. Simulations show that erosion of the upper A.R. can account for 73% of the water discharge increase. Dredging in the lower A.R. between 1932 and 1950 can account for 35% of the water discharge increase, and was also an important control on shear stress distribution. The lower M.R. was slightly erosional during this period, and therefore hindered the A.R. discharge increase. Significant lacustrine delta deposition in A.R. had little effect on partitioning. These findings highlight the importance of A.R. enlargement processes on avulsion dynamics at this site. Given the essential nature of this river junction to the society, transportation, and commerce of the United States, improved attribution of discharge increases may lead to future management strategies that are broadly impactful.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Altogether, this work provides a unique analysis of cloud and radiation properties based on high-resolution shipborne observations, which can be used to assist future model evaluation and development.

58 GEOSCIENCES↗
DOE OSTI2022

n-Butanol or isobutanol as a value-added fuel additive to inhibit microbial degradation of stored gasoline

Biofouling of gasoline can occur during fuel storage caused by bacteria and fungi that form a biofilm at a fuel/water interface and that produce organic acids and sulfides. Fuel additives are applied to gasoline to prevent biofouling but are relatively expensive, are not always effective against biofilms, and do not contribute to the combustibility of gasoline. Bio-isobutanol is an approved, certified advanced biofuel and is added up to 16% ( v/v ) in gasoline blends “iBut16”; n-butanol blends are currently under review. Microorganisms are inhibited by n-butanol or isobutanol when the aqueous concentration reaches >2-3% (w/ v ). We determined that n-butanol partitions into the aqueous phase of a model gasoline/water system reaching concentrations of 42 g/L and up to 48 g/L from gasoline blends at 10% and 24% ( v/v ), respectively. Likewise, isobutanol blended in gasoline at 10% and 24% ( v/v ) partitioned into an aqueous phase at 45 g/L and 53 g/L, respectively. Several bacterial and fungal strains that originate from fuel storage tanks, or are known to be solvent tolerant, were evaluated for their potential growth in a range of n- and isobutanol concentrations. Growth rates for all strains tested were reduced by 40–100% relative to untreated controls in n- and isobutanol concentrations of 1.5 and 2.0% ( v/v ). No observable growth occurred for any of the microorganisms in solvent concentrations at 3.0% ( v/v ). T amphiphilic and chaotropic properties of n- or isobutanol help them inhibit microbial growth and could serve as effective biocides during fuel storage as well as being valuable fuel additives.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Bridging Aromatic/Antiaromatic Units: Recent Advances in Aromaticity and Antiaromaticity in Main-group and Transition-Metal Clusters from Bonding and Magnetic Analyses

Synthetic exploration and theoretical characterization of metal clusters are actively developing branches of modern inorganic chemistry. Advances in these areas constantly expand the rich structural diversity of viable species, allowing a detailed study of the fundamental characteristics of bench-stable compounds. In this minireview, we summarize recent achievements in synthesis and computational analyses of main-group and heterometallic clusters containing multiple aromatic/antiaromatic units. These systems range from bare clusters to ligand-decorated aggregates, providing a fundamental understanding of the aromaticity and antiaromaticity concepts in species exhibiting unprecedented shapes and composition. The review gives a comprehensive summary of bonding and magnetic response properties of such systems deciphered from the Adaptive Natural Density Partitioning (AdNDP) approach and induced magnetic field analyses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Soil organic matter is principally root derived in an Ultisol under oak forest

To a large degree, the sources and stability of soil organic carbon remain poorly constrained. A clear understanding of links among the components of the soil C cycle is hampered by the complexity of the system as well as challenges associated with partitioning bulk soil C into meaningful fractions. A large accidental 14 CO 2 release at the Oak Ridge Reservation in Tennessee, USA provided a strong label pulse into adjacent, well-studied oak forests, resulting in highly elevated Δ 14 C values in leaf litter (~1000‰) and roots (~260–450‰). A four-year manipulative study was conducted to determine the relative contribution of litter versus roots to the bulk mineral soil C pool, as well as to free light, occluded light and heavy fractions. The heavy fraction was further split into fractions with densities of 1.7–2.4 g cm –3 and >2.4 g cm –3 to test the homogeneity of the mineral-associated fraction of C. Substantial concentrations of label were detected in all soil fractions within a year of the 14 CO 2 release, indicating rapid incorporation of newly fixed photosynthates in all fractions of soil organic C, regardless of differences in stability inferred by previous work. This rapid incorporation of label occurred only in treatments where roots were labeled, indicating that roots are the major source of inputs to mineral soil C stocks at these sites. Separation of the heavy fraction into subfractions of intermediate (1.7–2.4 g cm –3 ) and high (>2.4 g cm –3 ) density indicated that both subfractions incorporated label at similar rates, despite significant differences in degree of microbial processing. In general, the rate of label incorporation suggested a much faster turnover for all fractions than indicated by natural radiocarbon abundance values. This study suggests that within each soil fraction there are portions of slow-cycling and fast-cycling materials, and the determination of an average turnover time or mean age is dependent on experimental approach. The rapid incorporation of label into all fractions within a year regardless of inferred stability implies a high degree of heterogeneity in all fractions regardless of how finely the soils are partitioned. Further refinement of the nature and drivers of this heterogeneity could yield important insights into the soil C cycle.

58 GEOSCIENCES↗
DOE OSTI2021

Modeling Data Movement Performance on Heterogeneous Architectures

The cost of data movement on parallel systems varies greatly with machine architecture, job partition, and nearby jobs. Performance models that accurately capture the cost of data movement provide a tool for analysis, allowing for communication bottlenecks to be pinpointed. Modern heterogeneous architectures yield increased variance in data movement as there are a number of viable paths for inter-GPU communication. In this paper, we present performance models for the various paths of inter-node communication on modern heterogeneous architectures, including the trade-off between GPUDirect communication and copying to CPUs. Furthermore, we present a novel optimization for inter-node communication based on these models, utilizing all available CPU cores per node. Finally, we show associated performance improvements for MPI collective operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Detecting multiple communities using quantum annealing on the D-Wave system

A very important problem in combinatorial optimization is the partitioning of a network into communities of densely connected nodes; where the connectivity between nodes inside a particular community is large compared to the connectivity between nodes belonging to different ones. This problem is known as community detection, and has become very important in various fields of science including chemistry, biology and social sciences. The problem of community detection is a twofold problem that consists of determining the number of communities and, at the same time, finding those communities. This drastically increases the solution space for heuristics to work on, compared to traditional graph partitioning problems. In many of the scientific domains in which graphs are used, there is the need to have the ability to partition a graph into communities with the “highest quality” possible since the presence of even small isolated communities can become crucial to explain a particular phenomenon. We have explored community detection using the power of quantum annealers, and in particular the D-Wave 2X and 2000Q machines. It turns out that the problem of detecting at most two communities naturally fits into the architecture of a quantum annealer with almost no need of reformulation. This paper addresses a systematic study of detecting two or more communities in a network using a quantum annealer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Seismo-Acoustic Wave Simulation for Earthquake-Generated Infrasound

It is well known that underground explosions or earthquakes can generate infrasound in the atmosphere. Seismoacoustic coupling between the ground motions and atmosphere is a key mechanism for infrasound generation. Epicentral infrasound which is direct response to epicentral ground motions are extensively studied for event detection and discrimination. Diffracted infrasound generated from Rayleigh waves are often observed and reported. Recent studies suggested the surface topography is also important for infrasound generation, and mountains or topographic peaks can act as effective secondary infrasound sources. In this study, we perform full 3-D seismoacoustic simulations to understand a coupled seismic and acoustic wave generation by an earthquake and energy partitioning across the solid Earthocean-atmosphere system. By including the effects of realistic topography, bathymetry, and earthquake focal mechanism, we provide quantitative information about seismoacoustic wavefields and secondary infrasound sources across the solid-water, solid-air, and water-air interfaces. Acoustic wave transmission across water-air interface is also investigated by using synthetic waveforms. Our study suggests that shallow seas near the coastline or over elevated seafloors can transmit significant amount of energy from acoustic waves in water and can be effective secondary infrasound sources.

58 GEOSCIENCES↗