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At least 1,063 records · Page 59

Transition to turbulence in plane channel flows

Results obtained from a numerical simulation of the final stages of transition to turbulence in plane channel flow are described. Three dimensional, incompressible Navier-Stokes equations are numerically integrated to obtain the time evolution of two and three dimensional finite amplitude disturbances. Computations are performed on CYBER-203 vector processor for a 32x51x32 grid. Results are presented for no-slip boundary conditions at the solid walls as well as for periodic suction blowing to simulate active control of transition by mass transfer. Solutions indicate that the method is capable of simulating the complex character of vorticity dynamics during the various stages of transition and final breakdown. In particular, evidence points to the formation of a lambda-shape vortex and the subsequent system of horseshoe vortices inclined to the main flow direction as the main elements of transition. Calculations involving periodic suction-blowing indicate that interference with a wave of suitable phase and amplitude reduces the disturbance growth rates.

Biringen, S.↗

Dark matter in the solar system

Many small bodies in the solar system, including planetary satellites, comets, and asteroids, have a surface component consisting at least in part of a very low albedo (0.06 or less) solid substance of neutral or red color in the wavelength region 0.3-2.5 microns. Laboratory spectra of organic residues from meteorites and mixtures with hydrous silicates suggest that complex mixtures of complex organic molecules (kerogens) together with aqueous alteration products of igneous minerals may be the source of the dark matter that is distributed so widely throughout the solar system.

Cruikshank, Dale P.↗

NextGen Future Safety Assessment Game

The successful implementation of the next generation infrastructure systems requires solid understanding of their technical, social, political and economic aspects along with their interactions. The lack of historical data that relate to the long-term planning of complex systems introduces unique challenges for decision makers and involved stakeholders which in turn result in unsustainable systems. Also, the need to understand the infrastructure at the societal level and capture the interaction between multiple stakeholders becomes important. This paper proposes a methodology in order to develop a holistic approach aiming to provide an alternative subject-matter expert (SME) elicitation and data collection method for future sociotechnical systems. The methodology is adapted to Next Generation Air Transportation System (NextGen) decision making environment in order to demonstrate the benefits of this holistic approach.

Ancel, Ersin↗

NextGen Future Safety Assessment Game

The successful implementation of the next generation infrastructure systems requires solid understanding of their technical, social, political and economic aspects along with their interactions. The lack of historical data that relate to the long-term planning of complex systems introduces unique challenges for decision makers and involved stakeholders which in turn result in unsustainable systems. Also, the need to understand the infrastructure at the societal level and capture the interaction between multiple stakeholders becomes important. This paper proposes a methodology in order to develop a holistic approach aiming to provide an alternative subject-matter expert (SME) elicitation and data collection method for future sociotechnical systems. The methodology is adapted to Next Generation Air Transportation System (NextGen) decision making environment in order to demonstrate the benefits of this holistic approach.

Ancel, Ersin↗

HIWRAP Radar Development for High-Altitude Operation on the NASA Global Hawk and ER-2

The NASA High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a solid-state transmitter-based, dual-frequency (Ka- and Ku-band), dual-beam (30 degree and 40 degree incidence angle), conical scan Doppler radar system, designed for operation on the NASA high-altitude (20 km) aircrafts, such as the Global Hawk Unmanned Aerial System (UAS). Supported by the NASA Instrument Incubator Program (IIP), HIWRAP was developed to provide high spatial and temporal resolution 3D wind and reflectivity data for the research of tropical cyclone and severe storms. With the simultaneous measurements at both Ku- and Ka-band two different incidence angles, HIWRAP is capable of imaging Doppler winds and volume backscattering from clouds and precipitation associated with tropical storms. In addition, HIWRAP is able to obtain ocean surface backscatter measurements for surface wind retrieval using an approach similar to QuikScat. There are three key technology advances for HIWRAP. Firstly, a compact dual-frequency, dual-beam conical scan antenna system was designed to fit the tight size and weight constraints of the aircraft platform. Secondly, The use of solid state transmitters along with a novel transmit waveform and pulse compression scheme has resulted in a system with improved performance to size, weight, and power ratios compared to typical tube based Doppler radars currently in use for clouds and precipitation measurements. Tube based radars require high voltage power supply and pressurization of the transmitter and radar front end that complicates system design and implementation. Solid state technology also significantly improves system reliability. Finally, HIWRAP technology advances also include the development of a high-speed digital receiver and processor to handle the complex receiving pulse sequences and high data rates resulting from multi receiver channels and conical scanning. This paper describes HIWRAP technology development for dual-frequency operation at high-altitudes using low peak power transmitters and pulse compression. The hardware will be described along with the methods and concepts for the system design. Finally, we will present recent preliminary results from flights on the NASA Global Hawk in support of the NASA Genesis and Rapid Intensification Processes (GRIP) field campaign, and on the NASA ER-2 as fixed nadir pointing mode for the NASA Global Precipitation Measurement (GPM) ground validation (GV) mission - Midlatitude Continental Convective Cloud Experiment (MC3E)

Li, Lihua↗

Unleashing the Power of Anaerobic–Phototrophic Membrane Bioreactors for Sustainable Bioregenerative Life Support

Using the core ideals of bioregenerative life support, an anaerobic–phototrophic membrane bioreactor (APMBR) has been designed and operated at NASA’s Kennedy Space Center to treat complex wastewaters with the goal of closing water and nutrient cycles on early planetary bases. The system combined the previously operated anaerobic membrane bioreactor and the phototrophic membrane bioreactor that have been detailed in presentations at previous ICES conferences. This newly combined system is able to treat complex wastewater with completely automated controls on a small footprint. The treatment of wastes in this APMBR is as follows: (1) the waste enters the anaerobic subsystem, where solids are hydrolyzed and carbon is removed via anaerobic digestion, (2) an ultrafiltration membrane is used to separate the solids and the recovered water, (3) the effluent from the anaerobic subsystem is fed to the phototrophic subsystem on command, (4) the algae–bacteria consortium aids in nitrification in the recovered water, and (5) an ultrafiltration membrane is used to separate the algae and the final recovered water. The recovered water from the APMBR is rich in nutrients, making it a sustainable source of fertilizer for downstream hydroponic systems. This conference paper will detail the design and operation of the APMBR as a bioregenerative alternative to physical–chemical systems or bag and storage systems. In this paper, data will be presented on subsystem water quality, membrane performance, and effluent quality. Overall, the APMBR has the ability to treat wastewater using a combination of biological and filtration technologies that allow for higher removal efficiencies, low consumable use, and small footprint.

Jason A. Fischer↗

Defect Thermodynamics and Transport Properties of Proton Conducting Oxide BaZr 1–x Y x O 3–δ (x ≤ 0.1) Guided by Density Functional Theory Modeling

Density functional theory-based thermodynamic modeling was performed to determine the effect of humidity and H 2 /O 2 gas pressure on the defect chemistry and transport properties of proton conducting oxide BaZr 1-x Y x O 3-δ (x ≤ 0.1) in the temperature range of 800–1200K, relevant for solid oxide fuel/electrolysis cell applications. The first-principles charge defect analysis was carried out to obtain the defect energetic ensembles as a function of Fermi level as well as the dependence of the hydration and oxidation reaction energies on complex defect-dopant configurations. It is shown that oxygen vacancies introduced to compensate for the extra Ba vacancies may cause a slight increase in the concentration of hydroxyl and proton species upon hydration of Ba deficient BaZr 1-x Y x O 3-δ , while the overall proton diffusivity is predicted to decrease with increased proton hopping barriers upon trapping near the Ba vacancies. The developed defect model is further demonstrated to be able to describe the bulk defect chemistry and transport properties of BaZr 0.9 Y 0.1 O 3-δ under the solid oxide cell operating conditions. Finally, the theoretical framework developed in this work further allows the inclusion of configurational, energetic and electronic characteristics of the defects that can be used as a complementary tool to experimental measurements for testing various mechanistic pathways or to provide essential mechanistic data.

36 MATERIALS SCIENCE↗

Point containment algorithms for constructive solid geometry with unbounded primitives

Here, we present several algorithms for evaluating point containment in constructive solid geometry (CSG) trees with unbounded primitives. Three algorithms are presented based on postfix, prefix, and infix notations of the CSG binary expression tree. We show that prefix and infix notations enable short-circuiting logic, which reduces the number of primitives that must be checked during point containment. To evaluate the performance of the algorithms, each algorithm was implemented in the OpenMC Monte Carlo particle transport code, which relies on CSG to represent solid bodies through which subatomic particles travel. Two sets of tests were carried out. First, the execution time to generate a rasterized image of a 2D slice of three CSG models of varying complexity was measured. Use of both prefix and infix notations offered significant speedup over the postfix notation that has traditionally been used in particle transport codes, with infix resulting in a 6 x reduction in execution time relative to postfix for a model of a tokamak fusion device. We then measured the execution time of neutron transport simulations of the same three models using each of the algorithms. The results and performance improvements reveal the same trends as for the rasterization test, with a 5.52 x overall speedup using the infix notation relative to the original postfix notation in OpenMC for the tokamak model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Developing Lanthanide-Nitrate Cluster Chemistry toward Rare Earth Separations

Nitrate-decorated hexamers with a [Ln 6 (μ 6 -O)(μ 3 –OH) 8 ] 8+ core have been reported for nearly every lanthanide ion and are used as precursors for the assembly of functional metal–organic frameworks. Yet, few studies have examined the correlation between the solution and solid-state species, and the formation of mixed-metal clusters. Toward this end, a series of homo- and heterometal lanthanide nitrate hexamers was prepared via pH adjustment of aqueous lanthanide nitrate solutions. Examination of the homometallic europium solutions using Small Angle X-ray Scattering and nESI-MS showed that lower order complexes dominate lanthanide speciation in nitrate media. Yet, powder X-ray diffraction data of the precipitated phase confirmed the formation of [Ln 6 (μ 6 -O)(μ 3 -OH) 8 (NO 3 ) 6 (H 2 O) 12 ]·2(NO 3 )·n(H 2 O), Ln 6 , for Ln = Eu and Tb. For heterometal systems, analysis of the solid-state product by ICP–MS showed the selective incorporation of the heavier rare earths into Ln 6 . Selectivity was quantified by calculating an average separation factor, which is defined as the ratio of recovery factors of both metals. Further examination of the luminescence behavior of mixed metal [Tb 6–x Eu x (μ 6 -O)(μ 3 -OH) 8 (NO 3 ) 6 (H 2 O) 12 ]·2(NO 3 )·n(H 2 O), with x = 1.1–3.6, showed that the relative intensities of the peaks at 489 nm (terbium, 5 D 4 → 7 F 6 ) and 690 nm (europium, 5 D 0 → 7 F 4 ) trend with the percent incorporation of europium and terbium into the cluster.

anions↗

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗

Potential-pH diagrams considering complex oxide solution phases for understanding aqueous corrosion of multi-principal element alloys

The potential-pH diagram, a graphical representation of the thermodynamically predominant reaction products in aqueous corrosion, is originally proposed for the corrosion of pure metals. The original approach only leads to stoichiometric oxides and hydroxides as the oxidation products. However, numerous experiments show that non-stoichiometric oxide scales are prevalent in the aqueous corrosion of alloys. In the present study, a room temperature potential-pH diagram considering oxide solid solutions, as a generalization of the traditional potential-pH diagram with stoichiometric oxides, is constructed for an FCC single-phase multi-principal element alloy (MPEA) based on the CALculation of PHAse Diagram method. The predominant reaction products, the ions in aqueous solution, and the cation distribution in oxides are predicted. The oxide solid solution is stabilized by the mixing free energy (or mixing entropy) and the stabilizing effect becomes more significant as the temperature increases. Consequently, solid solution oxides are stable in large regions of the potential-pH diagram and the mixing free energy mostly affects the equilibrium composition of the stable oxides, while the shape of stable regions for oxides is mostly determined by the structure of the stable oxides. Agreements are found for Ni 2+ , Fe 2+ , and Mn 2+ between the atomic emission spectroelectrochemistry measurements and thermodynamic calculations, while deviations exist for Cr 3+ and Co 2+ possibly due to surface complexation with species such as Cl - and the oxide dissolution. By incorporating the solution models of oxides, the current work presents a general and more accurate way to analyze the reaction products during aqueous corrosion of MPEAs.

Materials Science↗

Ion Transport in Batteries with Polymer Electrolytes

We discuss polymer electrolytes for use in rechargeable lithium batteries. Polymer electrolytes have the potential to enable batteries with lithium metal anodes. These batteries have significantly higher theoretical energy densities than current lithium-ion batteries. We consider binary mixtures of polymers and salts. We also cover more complex systems such as polymer electrolytes swollen with a solvent (gel polymer electrolytes) and microphase separated polymer electrolytes. By covalently attaching the anions to the chains in a polymer solid, one obtains a single-ion conductor. We mainly focus on experiments wherein the polymer electrolyte is placed between two lithium metal electrodes. These experiments enable the determination of three transport parameters, ionic conductivity, salt diffusion coefficient, and transference number, and the thermodynamic factor. The properties of dry polymer electrolytes are contrasted with those of gel polymer electrolytes. The gel systems exhibit higher conductivity while the dry systems exhibit superior mechanical properties. We discuss interfacial impedance when lithium metal is contacted with polymer electrolytes and the importance of coulombic efficiency.

Yu, Xiaopeng↗

A hybrid smoothed-particle hydrodynamics model of oxide skins on molten aluminum

A computational model of aluminum melting is proposed which captures both the thermal fluid-solid phase transition and the mechanical effects of oxidation. The model hybridizes ideas from smoothed particle hydrodynamics and bonded particle models to simulate both hydrodynamic flows and solid elasticity. Oxidation is represented by dynamically adding and deleting spring-like bonds between surface fluid particles to represent the formation and rupture of the oxide skin. Various complex systems are simulated to demonstrate the adaptability of the method and to illustrate the significant impact of skin properties on material flow. As a result, initial comparison to experiments of a melting aluminum cantilever highlights that the computational model can reproduce key qualitative features of aluminum relocation.

Clemmer, Joel Thomas↗

Chromium segregation-induced oxide evolution in Ni-10Cr alloys during high-temperature oxidation

The oxidation behavior of a Ni-10(wt%)Cr alloy under high-temperature O 2 conditions is investigated using transmission electron microscopy and first-principles calculations. Results reveal that chromium segregation plays a central role in driving the evolution of complex oxide phase structures during oxidation. At low Cr concentrations, Cr preferentially segregates to NiO grain boundaries or internal pores, substituting for Ni atoms and forming Ni(Cr)O solid solutions. As Cr content increases, enhanced diffusion promotes Cr penetration into the NiO lattice, leading to the formation of multiphase oxide structures. First-principles modeling corroborates these findings: at low Cr concentrations, Cr atoms favor surface and grain-boundary segregation, while higher concentrations lead to Cr aggregation within the NiO bulk. Furthermore, the integrated experimental-theoretical approach provides atomistic insights into Cr-mediated mass transport mechanisms during alloy oxidation and offers valuable guidance for controlling oxide growth kinetics and phase stability in Ni-Cr alloys, with implications for improving oxidation resistance in high-temperature structural applications.

36 MATERIALS SCIENCE↗

Supported Metal Pair-Site Catalysts

Complexes with neighboring metal centers in isolated pairs and their analogues on surfaces are drawing increasing attention as catalysts. These include molecular homogeneous catalysts incorporating various ligands, enzymes, and solids that include pairs of metal atoms mounted on supports. Catalysts in this broad class are active for numerous reactions and offer unexplored opportunities to address challenging reactions, such as oxidation of methane and oxidation of water in artificial photosynthesis. The subject of supported metal pair-site catalysts is in its infancy, facing challenges in (a) precise synthesis, (b) structure determination at the atomic scale, and (c) stabilization in reactive atmospheres. In this Perspective, we summarize key characteristics of molecular and enzymatic catalysts that incorporate neighboring metal centers and build on this foundation to assess the emerging literature of metal pair-site catalysts on various supports. The supported catalysts include those synthesized by anchoring molecular dinuclear precursors to support surfaces and those synthesized by selective formation of dinuclear surface species from mononuclear surface species. Examples of metals in this class are rhodium and iridium, and examples of supports are MgO and Fe 2 O 3 . We summarize characterization of these materials by electron microscopy and spectroscopy, emphasizing atomic-resolution aberration-corrected scanning transmission electron microscopy and spectroscopies that provide atomic-scale structural information and allow characterization of functioning catalysts, especially X-ray absorption spectroscopy. Finally, we list some opportunities for research, including suggestions that might lead to structurally well-defined supported metal pair-sites with new catalytic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular speciation controls arsenic and lead bioaccessibility in fugitive dusts from sulfidic mine tailings

Communities nearby mine wastes in arid and semi-arid regions are potentially exposed to high concentrations of toxic metal(loid)s from fugitive dusts deriving from impoundments. To assess the relation between potentially lofted particles and human health risk, we studied the relationship between pharmacokinetic bioaccessibility and metal(loid) molecular speciation for mine tailings dust particulate matter (PM), with elevated levels of arsenic and lead (up to 59 and 34 mmol kg -1 , respectively), by coupling in vitro bioassay (IVBA) with X-ray absorption spectroscopy (XAS). Mine tailing efflorescent salts (PM ES ) and PM from the surface crust (0–1 cm, PM SC ) and near surface (0–25 cm) were isolated to <10 μm and <150 μm effective spherical diameter (PM 10 and PM 150 ) and reacted with synthetic gastric and lung fluid for 30 s to 100 h to investigate toxic metal(loid) release kinetics. Bioaccessible (BAc) fractions of arsenic and lead were about 10 and 100 times greater in gastric than in lung fluid simulant, respectively, and 10–100% of the maximum gastric BAc from PM 10 and PM 150 occurred within 30 s, with parabolic dissolution of fine, highly-reactive particles followed by slower release from less soluble sources. Evaporite salts were almost completely solubilized in gastric-fluid simulants. Arsenate within jarosite and sorbed to ferrihydrite, and lead from anglesite, were identified by XAS as the principal contaminant sources in the near surface tailings. In the synthetic lung fluid, arsenic was released continuously to 100 h, suggesting that residence time in vivo must be considered for risk determination. Analysis of pre- and post-IVBA PM indicated the release of arsenic in lung fluid was principally from arsenic-substituted jarosite, whereas in synthetic gastric fluid arsenic complexed on ferrihydrite surfaces was preferentially released and subsequently repartitioned to jarosite-like coordination at extended exposures. Lead dissolved at 30 s was subsequently repartitioned back to the solid phase as pyromorphite in phosphate rich lung fluid. The bioaccessibility of lead in surface tailings PM was limited due to robust sequestration in plumbojarosite. Kinetic release of toxic elements in both synthetic biofluids indicated that a single IVBA interval may not adequately describe release dynamics.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

AI-powered exploration of molecular vibrations, phonons, and spectroscopy

The vibrational dynamics of molecules and solids play a critical role in defining material properties, particularly their thermal behaviors. However, theoretical calculations of these dynamics are often computationally intensive, while experimental approaches can be technically complex and resource-demanding. Recent advancements in data-driven artificial intelligence (AI) methodologies have substantially enhanced the efficiency of these studies. This review explores the latest progress in AI-driven methods for investigating atomic vibrations, emphasizing their role in accelerating computations and enabling rapid predictions of lattice dynamics, phonon behaviors, molecular dynamics, and vibrational spectra. Key developments are discussed, including advancements in databases, structural representations, machine-learning interatomic potentials, graph neural networks, and other emerging approaches. Compared to traditional techniques, AI methods exhibit transformative potential, dramatically improving the efficiency and scope of research in materials science. The review concludes by highlighting the promising future of AI-driven innovations in the study of atomic vibrations.

Han, Bowen [Oak Ridge National Laboratory (ORNL), ↗

Effective optimization of atomic decoration in giant and superstructurally ordered crystals with machine learning

Crystals with complicated geometry are often observed with mixed chemical occupancy among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar systems possessing exact occupancy on all the sites can exhibit superstructural ordering, dramatically inflating the unit cell size. In this work, a crystal graph convolutional neural network (CGCNN) is used to predict optimal atomic decorations on fixed crystalline geometries. This is achieved with a site permutation search (SPS) optimization algorithm based on Monte Carlo moves combined with simulated annealing and basin-hopping techniques. Our approach relies on the evidence that, for a given chemical composition, a CGCNN estimates the correct energetic ordering of different atomic decorations, as predicted by electronic structure calculations. This provides a suitable energy landscape that can be optimized according to site occupation, allowing the prediction of chemical decoration in crystals exhibiting mixed or disordered occupancy, or superstructural ordering. Verification of the procedure is carried out on several known compounds, including the superstructurally ordered clathrate compound Rb8Ga27Sb16 and vacancy-ordered perovskite Cs2SnI6, neither of which was previously seen during the neural network training. In addition, the critical temperature of an order–disorder phase transition in solid solution CuZn is probed with our SPS routines by sampling site configuration trajectories in the canonical ensemble. This strategy provides an accurate method for determining favorable decoration in complex crystals and analyzing site occupation at unprecedented speed and scale.

Chemistry↗