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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Comparison of Homogeneous and Heterogeneous Uranium Metal-Water Systems using Calculated and Experimental Critical Data

Heterogeneous effects of fissile units latticed in water has been documented in several forms in commonly referenced handbooks and guides. Many of these documents provide guidance for when heterogeneous systems are more reactive than their homogenous counterparts if controlling fissile mass or volume. This information provides insight into when heterogeneity should be considered for conservatism, however this information is not always displayed in a manner that is comparable to commonly referenced data, such as critical curves based on spherical systems. This paper aims to provide a juxtaposition of homogenous and heterogeneous uranium metal-water systems using both experimental and calculated critical data displayed in the format of commonly referenced critical curves. This format allows for easy comparison between the two systems against parameters that are often considered for single unit analysis such as: uranium density, fissile mass, system volume, and total system mass (fissile mass plus moderator mass). Calculated critical spherical systems provide an equal comparison between latticed geometry types as the latticed array can be physically cut off or restricted in the same manner in each series of models, which is not true for experimental values. Additionally, enrichment of the latticed units can be made uniform in the calculated systems, which is difficult to achieve when referencing experimental data of varying latticed geometries. A comparison of calculated critical values and available experimental values is provided to show how these parameters can impact the critical spherical system result.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Insights into Molecular Magnetism in Metal–Metal Bonded Systems as Revealed by a Spectroscopic and Computational Analysis of Diiron Complexes

A pair of bimetallic compounds featuring Fe–Fe bonds, [Fe( i PrNPPh 2 ) 3 FeR] (R = PMe 3 , ≡N t Bu), have been investigated using High-Frequency Electron Paramagnetic Resonance (HFEPR) as well as field- and temperature-dependent 57 Fe nuclear γ resonance (Mössbauer) spectroscopy. To gain insight into the local site electronic structure, we have concurrently studied a compound containing a single Fe(II) in a geometry analogous to that of one of the dimer sites. Our spectroscopic studies have allowed for the assessment of the electronic structure via the determination of the zero-field splitting and 57 Fe hyperfine parameters for the entire series. We also report on our efforts to correlate structure with physical properties in metal–metal bonded systems using ligand field theory guided by quantum chemical calculations. Through the insight gained in this study, we discuss strategies for the design of single-molecule magnets based on polymetallic compounds linked via direct metal–metal bonds.

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

Viscosity bounds in liquids with different structure and bonding types

Recently, it was realized that liquid viscosity has a lower bound which is nearly constant for all liquids and is governed by fundamental physical constants. This was supported by experimental data in noble and molecular liquids. Here, we perform large-scale molecular dynamics simulations to ascertain this bound in two other important liquid types: the ionic molten salt system LiF and metallic Pb. We find that these ionic and metallic systems similarly have lower viscosity bounds corresponding to the minimum of kinematic viscosity of ∼ 10 − 7 m 2 / s . We show that this agrees with experimental data in other systems with different structures and bonding types, including noble, molecular, metallic, and covalent liquids. This expands the universality of viscosity bounds into the main system types known. Published by the American Physical Society 2024

Materials Science↗
DOE OSTI2026

An Activity-Based Sensing Approach to Monitor Nanomaterial-Promoted Changes in Labile Metal Pools in Living Systems

Metal-based nanoparticles are a promising class of materials for diagnosis and treatment of cancer and other diseases. However, mechanisms of action of these nanomedicines remain insufficiently understood due in large part to our limited understanding of the dynamic equilibria between solid metal nanoparticles and labile metal ions generated from these nanoparticles within complex biological milieus. Here, we apply activitybased sensing to directly identify and investigate the fate of labile copper pools with metal and oxidation state-specificity generated by anticancer copper nanomedicines. We found that treatment of cells with copper-releasing nanoparticles alter labile Cu(I)/Cu(II) ratios through an increase in labile Cu(II), while overall labile copper levels decrease. Labile copper release triggers compensatory responses in two major antioxidant pathways, glutathione (GSH) and nuclear factor erythroid 2-related factor 2 (NRF2), as well as in metal homeostasis to limit copper availability via regulation of copper export (ATP7B) and copper import (CTR1) proteins. These findings establish the value of activity-based sensing as a generalizable approach for labile metal imaging to help decipher molecular mechanisms of bioactive metal nanoparticles and guide the development of more effective nanomedicine diagnostics and therapies to target metal-dependent disease vulnerabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning pipeline to predict defect behavior in metallic alloy systems

The interaction between defect and solute atoms is critical to the thermodynamic and kinetic behavior of metallic alloys under exposure to high-energy radiation, causing irradiation damage in materials. Radiation can generate non-equilibrium concentrations of point defects such as vacancies and interstitials. The excess point defects not only accelerate diffusional processes such as precipitation that cause radiation embrittlement, but also change the pathway of phase transformations, including nucleation processes. Understanding these defect behaviors is complicated by the challenge and complexity of addressing each possible local and discrete distribution of environments and chemical interactions around targeted defects-solute or solute-solute complexes. To resolve the challenge, machine learning regression techniques have emerged as powerful tools that can train and construct an energy model to accurately describe the chemical interactions of solutes and defects. In Fiscal Year 2022, the work focused on the workflow development and demonstration using machine learning regression, density functional theory, cluster expansion, and Monte Carlo simulation to predict the effects of ternary solute elements (e.g., aluminum and molybdenum) and point defects on the Cr-rich $\alpha^{\prime}$ precipitation in multicomponent FeCr model alloys. The computational outcomes include the prediction of the ternary phase diagram, vacancy formation energy for different compositions, and the effect of vacancies on the nucleation of Cr-rich clusters. The simulations predict a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from $\alpha^{\prime}$ precipitates. Additionally, the simulations show the formation of Cr-vacancy clusters as the initial nuclei for stable nucleation and growth of $\alpha^{\prime}$ particles. The results demonstrate important outcomes and applications of using machine learning pipeline to study model or commercial alloys with multicomponent solute species and point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Nature of Non-Adiabatic Electron-Ion Forces in Liquid Metals

We report that an accurate description of electron-ion interactions in materials is crucial for our understanding of their equilibrium and non-equilibrium properties. Here, we assess the properties of frictional forces experienced by ions in non-crystalline metallic systems, including liquid metals and warm dense plasmas, that arise from electronic excitations driven by the nuclear motion due to the presence of a continuum of low-lying electronic states. To this end, we perform detailed ab-initio calculations of the full friction tensor that characterizes the set of friction forces. The nonadiabatic electron-ion interactions introduce hydrodynamic couplings between the ionic degrees of freedom, which are sizeable between nearest neighbors. The friction tensor is generally inhomogeneous, anisotropic and non-diagonal, especially at lower densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Antibiotic resistance and host immune system-induced metal bactericidal control are key factors for microbial persistence in the developing human preterm infant gut microbiome

The human gut microbiome, which develops and stabilizes during the early stages of infant life, plays an essential role in host health through the production of metabolic resources and the stimulation and training of the immune system. To study colonization and community functional dynamics of the microbiota based on responses to host immune processes during the normal and dysbiotic establishment of the gut, metaproteomics was conducted on 91 fecal samples collected over the first 90 days of life from 17 hospitalized premature infants. Microbial responses to antibiotic administration and host-imposed metal bactericidal control correlated with community assembly and resiliency of microbes in the developing preterm gut. Specifically, proteins related to antibiotic resistance and metal homeostasis mechanisms were predominant in persisting members in the infant gut environment over the first several weeks of life. Overall, this metaproteomics study provides a unique approach to examine the temporal expansion and resilience of microbial colonization, as it allows simultaneous examination of both host and microbial metabolic activities. Understanding the interplay between host and microbes may elucidate the microbiome’s potential immunomodulatory roles relevant to necrotizing enterocolitis and other dysbiotic conditions in preterm infants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Mining for Metal–Organic Systems: Chemistry Frontiers of Th-, U-, and Zr-Materials

The conceptual framework presented in this Perspective overviews the design principles of innovative thorium-based materials that could address urgent needs of the medicinal, nuclear energy, and waste remediation sectors from the lens of zirconium and uranium analogs. We survey the intersections of Zr, Th, and U chemistry with a focus on how the intrinsic behavior of each metal translates to broader material properties, including, but not limited to, structural and topological diversity, preferential metal–ligand binding, and reactivity. On the example of several classes of materials, including organometallic complexes, polyoxometalates, and the primary focus of this Perspective, metal–organic frameworks (MOFs), the design principles that govern the preparation of Zr-, Th-, and U-compounds, including oxophilicity, variation in oxidation states, and stable coordination environments have been considered. Further, we highlight how the impact of the mentioned variables may shift throughout the progression from discrete molecular systems to extended structures. We discuss the common assumption that zirconium-organic materials are typically considered a close analog of thorium-based congeners in areas such as material design and preparation. Through consideration of fundamental chemistry principles, we shed light on the relationships between Zr-, Th-, and U-based materials and highlight how a critical analysis of their distinct properties can be used to target a desired material performance. Finally, we provide a detailed understanding of Th-based materials chemistry by anchoring their fundamental properties between two well-studied reference points, zirconium- and uranium-containing analogs.

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

NDT System for Metal Components in Concrete Structures

The goal of this SBIR program is to develop new NDT technology based on the innovative use of magnetic sensors designed specifically for ECT (Eddy Current Testing) of steel reinforcements in concrete structures. The Phase IIA goal is to expand the R&D accomplished in Phase II, such that the probe system is more capable, and the inspection system is more flexible.

42 ENGINEERING↗
DOE OSTI2024

Noise reduction of stochastic density functional theory for metals

Density Functional Theory (DFT) has become a cornerstone in the modeling of metals. However, accurately simulating metals, particularly under extreme conditions, presents two significant challenges. First, simulating complex metallic systems at low electron temperatures is difficult due to their highly delocalized density matrix. Second, modeling metallic warm-dense materials at very high electron temperatures is challenging because it requires the computation of a large number of partially occupied orbitals. This study demonstrates that both challenges can be effectively addressed using the latest advances in linear-scaling stochastic DFT methodologies. Despite the inherent introduction of noise into all computed properties by stochastic DFT, this research evaluates the efficacy of various noise reduction techniques under different thermal conditions. Our observations indicate that the effectiveness of noise reduction strategies varies significantly with the electron temperature. Furthermore, we provide evidence that the computational cost of stochastic DFT methods scales linearly with system size for metal systems, regardless of the electron temperature regime.

Chemistry↗
DOE OSTI2023

Pegasus IV: Discovery and Spectroscopic Confirmation of an Ultra-faint Dwarf Galaxy in the Constellation Pegasus

We report the discovery of Pegasus IV, an ultra-faint dwarf galaxy found in archival data from the Dark Energy Camera processed by the DECam Local Volume Exploration Survey. Pegasus IV is a compact, ultra-faint stellar system ( pc; M $_{V}$ = −4.25 ± 0.2 mag) located at a heliocentric distance of . Based on spectra of seven nonvariable member stars observed with Magellan/IMACS, we confidently resolve Pegasus IV’s velocity dispersion, measuring km s$^{−1}$ (after excluding three velocity outliers); this implies a mass-to-light ratio of for the system. From the five stars with the highest signal-to-noise spectra, we also measure a systemic metallicity of [Fe/H] = dex, making Pegasus IV one of the most metal-poor ultra-faint dwarfs. We tentatively resolve a nonzero metallicity dispersion for the system. These measurements provide strong evidence that Pegasus IV is a dark-matter-dominated dwarf galaxy, rather than a star cluster. We measure Pegasus IV’s proper motion using data from Gaia Early Data Release 3, finding (μ $_{α*}$, μ $_{δ}$) = (0.33 ± 0.07, −0.21 ± 0.08) mas yr$^{−1}$. When combined with our measured systemic velocity, this proper motion suggests that Pegasus IV is on an elliptical, retrograde orbit, and is currently near its orbital apocenter. Lastly, we identify three potential RR Lyrae variable stars within Pegasus IV, including one candidate member located more than 10 half-light radii away from the system’s centroid. The discovery of yet another ultra-faint dwarf galaxy strongly suggests that the census of Milky Way satellites is still incomplete, even within 100 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Adsorption cooling system using metal organic frameworks

A highly adsorptive structure, includes: a substrate; and a metal-organic framework (MOF) comprising a plurality of metal atoms coordinated to a plurality of organic spacer molecules; wherein the MOF is coupled to at least one surface of the substrate, wherein the MOF is adapted for adsorbing and desorbing a refrigerant under predetermined thermodynamic conditions. The refrigerant includes one or more materials selected from the group consisting of: acid halides, alcohols, aldehydes, amines, chlorofluorocarbons, esters, ethers, fluorocarbons, perfluorocarbons, halocarbons, halogenated aldehydes, halogenated amines, halogenated hydrocarbons, halomethanes, hydrocarbons, hydrochlorofluorocarbons, hydrofluoroethers, hydrofluoroolefins, inorganic gases, ketones, nitrocarbon compounds, noble gases, organochlorine compounds, organofluorine compounds, organophosphorous compounds, organosilicon compounds, oxide gases, refrigerant blends and thiols.

Baumann, Theodore F.↗
DOE OSTI2023

Adsorption cooling system using metal organic frameworks

A highly adsorptive structure includes: a substrate; and a metal-organic framework (MOF) comprising a plurality of metal atoms coordinated to a plurality of organic spacer molecules; wherein the MOF is coupled to at least one surface of the substrate, wherein the MOF is configured to adsorb and desorb a refrigerant under predetermined thermodynamic conditions. The refrigerant includes one or more materials selected from the group consisting of: acid halides, alcohols, aldehydes, amines, chlorofluorocarbons, esters, ethers, fluorocarbons, perfluorocarbons, halocarbons, halogenated aldehydes, halogenated amines, halogenated hydrocarbons, halomethanes, hydrocarbons, hydrochlorofluorocarbons, hydrofluoroethers, hydrofluoroolefins, inorganic gases, ketones, nitrocarbon compounds, noble gases, organochlorine compounds, organofluorine compounds, organophosphorous compounds, organosilicon compounds, oxide gases, refrigerant blends and thiols.

Baumann, Theodore F.↗
DOE OSTI2022

Uptake and speciation of trace metal inputs to Wetland Soils from Illinois and South Carolina and Stream Sediments from Tennessee

Metals occur in all ecosystems, although their concentrations vary depending on their natural geologic conditions and surrounding human activities. In addition to metals intrinsically present from the geology of a particular system, metals can enter environmental systems from a wide variety of natural and anthropogenic sources, such as sediment re-suspension, mining operations, industrial processes, agricultural activities, and atmospheric deposition. While metals can be toxic at high concentrations, some metals serve as essential micronutrients for biogeochemical processes. Metal transport and availability in engineered and natural water systems depend on processes of adsorption/desorption, oxidation/reduction, dissolution/precipitation, and ligand complexation. Insights into the speciation of metals and their bioavailability will also help advance understanding of the roles of metals in the biogeochemical cycling of nutrients. We conducted batch experiments under anoxic conditions on soils and sediments collected from three different natural aquatic systems to understand their response to influxes of dissolved Cu, Ni and Zn. While soils and sediments from all sites could strongly bind added trace metals, there were substantial differences in trace metal uptake trends between different sites, especially for Cu. There was no distinct correlation between trace metal uptake and the total organic matter, iron, and sulfur content present in the samples. X-ray absorption spectroscopy indicated that the speciation of the freshly added metals taken up by the solids differs substantially from the speciation of the metals originally present in unamended samples. Cu sulfides dominated speciation at low loadings (1 µmol/g), whereas complexation to thiol groups and formation of metallic Cu governed speciation at high loadings (10 µmol/g). For Ni and Zn, adsorption to mineral surfaces and organic matter governed their speciation in materials from most sites. This study suggests that the background speciation of metals in natural aquatic systems is a poor predictor of the speciation and lability of metals introduced to terrestrial aquatic systems from anthropogenic or natural processes. Our findings imply that geochemical processes controlling trace metal speciation may vary considerably with metal loading in different natural systems. Data are provided for marsh wetland soils at Argonne National Laboratory (Marsh 1 and Marsh 2), riparian wetland soils (Riparian 1 and Riparian 2) in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments (Stream 1 and Stream 2) from East Fork Poplar Creek near Oak Ridge National Laboratory. Data package includes the results of trace metal uptake experiments conducted on the selected sites for determining their capacity to immobilize metals under different loadings. XANES spectra for Cu, Ni, ad Zn at different loadings are included in the package. The abundance of different trace metal species obtained using linear combination fitting in ATHENA are also included in the data.

54 ENVIRONMENTAL SCIENCES↗