Ternary ACd 4 P 3 (A = Na, K) Nanostructures via a Hydride Solution-Phase Route
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A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.
There has been an increased focus on the overall accuracy and grid convergence of Reynolds-averaged Navier-Stokes (RANS)-based transition models from the recent AIAA and NATO-AVT workshops. Even though satisfactory grid convergence could be achieved for simple two-dimensional flow configurations, it required mesh counts that are substantially larger than those used in typical applications. In this paper, we focus our efforts on understanding how the grid resolution and topology influences the accuracy and convergence of results by studying the Schubauer and Skramstad flat-plate configuration and the NLF-0416 airfoil at an angle of attack equal to five degrees using FUN3D, a second-order finite-volume code. By focusing on these cases, we can analyze both natural and separation-induced transition scenarios. Multiple grid refinement strategies are investigated. First, we determine the relative effectiveness of zonal streamwise refinement in the transition region within structured grids as an alternative to the costly option of globally uniform refinement of a baseline grid. We also complement this zonal technique by globally varying the wall-normal resolution keeping the streamwise resolution fixed. The zonal streamwise refinement can accurately model natural transition in a flat-plate boundary layer and separation-induced transition, but struggles to accurately model natural transition in airfoil flows. A series of unstructured prismatic grids that have similar node counts and viscous wall spacings as the structured hexahedral grids are also tested, and they do not achieve grid convergence until an extremely fine resolution. Last, we employ adjoint-based unstructured grid adaptation in FUN3D to natural and separation-induced transition on the NLF-0416 airfoil. The adjoint-based refinement process converges to the same solution as the baseline family of structured grids, but leads to smaller errors on coarser grids.
There has been an increased focus on the overall accuracy and grid convergence of Reynolds-averaged Navier-Stokes (RANS)-based transition models from the recent AIAA and NATO-AVT workshops. Even though satisfactory grid convergence could be achieved for simple two-dimensional flow configurations, it required mesh counts that are substantially larger than those used in typical applications. In this paper, we focus our efforts on understanding how the grid resolution and topology influences the accuracy and convergence of results by studying the Schubauer and Skramstad flat-plate configuration and the NLF-0416 airfoil at an angle of attack equal to five degrees using FUN3D, a second-order finite-volume code. By focusing on these cases, we can analyze both natural and separation-induced transition scenarios. Multiple grid refinement strategies are investigated. First, we determine the relative effectiveness of zonal streamwise refinement in the transition region within structured grids as an alternative to the costly option of globally uniform refinement of a baseline grid. We also complement this zonal technique by globally varying the wall-normal resolution keeping the streamwise resolution fixed. The zonal streamwise refinement can accurately model natural transition in a flat-plate boundary layer and separation-induced transition, but struggles to accurately model natural transition in airfoil flows. A series of unstructured prismatic grids that have similar node counts and viscous wall spacings as the structured hexahedral grids are also tested, and they do not achieve grid convergence until an extremely fine resolution. Last, we employ adjoint-based unstructured grid adaptation in FUN3D to natural and separation-induced transition on the NLF-0416 airfoil. The adjoint-based refinement process converges to the same solution as the baseline family of structured grids, but leads to smaller errors on coarser grids.
Physics-informed neural networks (PINNs) based machine learning is an emerging framework for solving nonlinear differential equations. However, due to the implicit regularity of neural network structure, PINNs can only find the flattest solution in most cases by minimizing the loss functions. In this paper, we combine PINNs with the homotopy continuation method, a classical numerical method to compute isolated roots of polynomial systems, and propose a new deep learning framework, named homotopy physics-informed neural networks (HomPINNs), for solving multiple solutions of nonlinear elliptic differential equations. The implementation of an HomPINN is a homotopy process that is composed of the training of a fully connected neural network, named the starting neural network, and training processes of several PINNs with different tracking parameters. The starting neural network is to approximate a starting function constructed by the trivial solutions, while other PINNs are to minimize the loss functions defined by boundary condition and homotopy functions, varying with different tracking parameters. These training processes are regraded as different steps of a homotopy process, and a PINN is initialized by the well-trained neural network of the previous step, while the first starting neural network is initialized using the default initialization method. Finally, several numerical examples are presented to show the efficiency of our proposed HomPINNs, including reaction-diffusion equations with a heart-shaped domain.
This new technology report will describe the laboratory development of a new and innovative solution for the removal and destruction of PCBs found in painted structures or within the binding or caulking material on structures. The technology incorporates a Bimetallic Treatment System (BTS) that extracts and degrades only the PCBs found on the facilities, leaving in most cases the structure virtually unaltered.
Coinage-metal chalcogenide clusters are widely studied for their attractive photoluminescence properties. Copper chalcogenides are especially promising, but are often confined to solid-state investigations due to their limited solution stability and the difficulty of synthesizing stable, well-defined clusters. Here, we investigate copper–sulfur clusters incorporating a small number of Cu atoms to elucidate fundamental atomic interactions, ground- and excited-state characteristics, and photophysical behavior in both solid and solution. We have synthesized the Cu6(4,6-dimethyl-2-mercaptopyrimidine)6 cluster in both neutral and charged states, Cu6 and Cu6-2H2+, respectively, by selective ligand protonation. The molecular structures are determined using single-crystal X-ray diffraction, while Cu K-edge X-ray absorption spectroscopy is used to probe Cu electronic structure differences arising from the ligand modification. Steady-state and pump-probe optical spectroscopy is used to investigate photophysical properties, interpreted using density functional theory methods. Both clusters exhibit good stability in the solid state and in solution and show characteristic near-infrared emission with microsecond lifetimes. Overall, the Cu6S6 clusters display favorable charge–transfer characteristics and show potential for further use in driving photochemical transformations.
We present a comprehensive study of the nuclear and magnetic structures of the mixed olivine solid solution series LiFe 1-x Co x PO 4 as well as their delithiated counterparts, for metal concentrations x = 0.2 - 0.6. Through neutron powder diffraction studies, we find that the LiFe 1-x Co x PO 4 series orders in the magnetic space group Pnma', consistent with their Li(Fe/Co)PO 4 parent structures. After chemical delithiation using peracetic acid, however, the removal of over 30% of the lithium from the lattice results in a transition from an A y -type to an A x -type antiferromagnetic structure. The magnetic space group consistent with A x antiferromagnetism was found to be Pn'm'a'. Interestingly, magnetic susceptibility measurements of both series reveal that delithiation increases the magnetic transition temperature, T N , from 50 K to 115 K. We find through analysis of the diffraction data that the unit cell parameters change linearly as a function of x; consequently, the exchange pathways between the Fe/Co magnetic cations are affected by the delithiation. Here, we discuss how exchange pathways, metal oxidation states, and d-orbital occupation all contribute to the observed magnetic symmetries and trends in T N in both series.
The rising power density in electronic systems requires thermal management solutions that are both high-performing and reliable. Porous materials such as Copper Inverse Opal (CuIOs) have unique structural features, including high permeability and high thermal conductivity, to enhance pool boiling performance. However, there is little understanding of the degradation mechanism of such porous materials under pool boiling conditions. In this study, samples of 10 ..mu..m thick CuIOs with 4.8 ..mu..m diameter, covering silicon substrate of area 11 mm x 11 mm, with various heated areas ranging from 2.5 mm x 2.5 mm to 10 mm x 10 mm, were tested in 100 degrees C deionized water at a constant heat flux of 110 Wcm -2 for 3-to-7 days. The combined effect of erosion and corrosion caused structural degradation of the CuIOs. The directly heated area had the most severe degradation while the edge of the heater and the unheated area showed progressively less degradation, maintaining some CuIOs structure even after the 7-day reliability test. Among all the tested samples with various heater sizes, the 2.5 mm x 2.5 mm heater sample - in which the heater size was designed to be comparable to the water bubble characteristic length - had the largest critical heat flux (CHF) up to 300 Wcm -2 with a superheat ~ 13 degrees C. Additionally, CuIOs with a smaller heated area performed better in terms of reliability. This study offers preliminary insights into CuIOs degradation mechanisms, contributing to the development of more robust thermal management solutions. We expect that electroless plating of CuIOs with gold (Au), nickel (Ni), and atomic layer deposition (ALD) aluminum oxide (Al 2 O 3 ) in combination with appropriate application-specific coolants will further improve the reliability and lifetime of the CuIOs.
The theoretical basis for well posed marching of a Parabolic Navier-Stokes (PNS) computational technique for supersonic flow is discussed and examples given to verify the analysis. It is demonstrated that stable computations can be made even with very small steps in the marching direction. The method is applied to cones at large angle of attack in high Reynolds number, supersonic flow. Streamline trajectories generated from the numerical solutions demonstrate the development of vortex structures on the lee side of the cone.
The theoretical basis for well posed marching of a Parabolic Navier-Stokes (PNS) computational technique for supersonic flow is discussed and examples given to verify the analysis. It is demonstrated that stable computations can be made even with very small steps in the marching direction. The method is applied to cones at large angle of attack in high Reynolds number, supersonic flow. Streamline trajectories generated from the numerical solutions demonstrate the development of vortex structures of the lee side of the cone. Previously announced in STAR as N83-22551
In situ structures of Platinum (Pt) nanoparticles (NPs) can be determined with graphene liquid cell transmission electron microscopy. Atomic-scale three-dimensional structural information about their physiochemical properties in solution is critical for understanding their chemical function. We here analyze eight atomic-resolution maps of small (<3 nm) colloidal Pt NPs. Their structures are composed of an ordered crystalline core surrounded by surface atoms with comparatively high mobility. 3D reconstructions calculated from cumulative doses of 8500 and 17,000 electrons/pixel, respectively, are characterized in terms of loss of atomic densities and atomic displacements. Less than 5% of the total number of atoms are lost due to dissolution or knock-on damage in five of the structures analyzed, whereas 10–16% are lost in the remaining three. Less than 5% of the atomic positions are displaced due to the increased electron irradiation in all structures. The surface dynamics will play a critical role in the diverse catalytic function of Pt NPs and must be considered in efforts to model Pt NP function computationally.
The checkerboard lattice has been proposed to host topological flat bands as a result of destructive interference among its various electronic hopping terms. However, it has proven challenging to realize experimentally due to the difficulty of isolating this structure from any significant out-of-plane bonding while maintaining structural integrity. Here, in this study, single crystals of Zr 2 CuSb 3 , a potential candidate for the checkerboard lattice, were synthesized using the solution (self-flux) method, and their structure was confirmed via x-ray diffraction. Electrical-transport measurements indicate metallic behavior with electron-dominated carriers. Angle-resolved photoemission spectroscopy reveals multiple electron pockets and significant k z broadening due to its large c axis and low dispersion features in k z . Density-functional theory (DFT) calculations further disentangle the contributions from each high-symmetry plane, providing a comprehensive characterization of electronic behavior. The DFT calculations were then used to determine the orbital contributions of the bands and detect the out-of-plane bonding which prevented the flat bands from forming.
Matrix algebra solution, using coordinate systems transformations, to boundary value problem for structures composed of shell elements
Previous coreflooding results and wettability analyses in our group show that injection of naphthenic-acid-enriched water can improve oil recovery over traditional waterflooding. This observation is still a subject of research efforts without a definitive explanation. Naphthenic acids (NA) have been reported to drive wettability alteration and increase the water–oil interface elasticity. These alterations depend on the NA carbon number and aqueous-phase salinity, among other conditions, as reported in the literature. Smart-water flooding (SWF) research often links recovery to the initial wettability condition, being higher for initially oil-wet rock. SWF refers to a technique in which the aqueous-phase ion composition or/and salinity are changed to maximize oil recovery. Given NAs’ complex solution behavior, selecting acid combinations that prompt oil recovery is a difficult objective. The aim of this research is to determine the effects of select naphthenic acids on the oil–water interfacial rheology and wettability alteration and how these interfacial effects are associated with oil recovery under spontaneous imbibition. NAs were selected based on their carbon number, molecular structure, and solubility in the saline solution used in this research. We aimed at exploring which NAs should be used to regulate interfacial properties so as to either increase oil recovery or accelerate production. Time-domain nuclear magnetic resonance, interfacial dilatational rheology, and liquid-bridge experiments, i.e., proxy of snap-off, were conducted. A baseline was established using results obtained with a previously tested sulfate-rich aqueous phase, shown to be effective in recovering oil. Results show that NA14 and N18 increase the water–oil interfacial viscoelasticity and induce interfacial healing but led to different recovery factors. N10, while effective at inducing water wetness in oil-wet rock, is ineffective at increasing the recovery factor. We concluded that wettability and oil–water interfacial rheology are not exclusive, and instead they can synergistically favor EOR benefits. Moreover, oil recovery benefits under spontaneous imbibition are shown to depend strongly on the initial wettability conditions.
Uranium alloys are attractive recycled nuclear fuels because of their high thermal conductivity (k) and fissile density; however, the effects of alloying elements on k remain unclear. Here, the electron thermal conductivity (k_e) of U-Pu-Zr compositions are calculated using density functional theory. The electronic structure is evaluated to understand the effects of plutonium (Pu) and zirconium (Zr) substitution on the k_e of ?-U. Alloys of up to 37.5 at. % Pu and 37.5 at. % Zr are examined. Two methods are applied to calculate k_e; we find that the accuracy of each method depends on the electronic and mass similarities between the solute and solvent atoms. Specifically, when the solute atom is similar in electronic structure and mass, the method that applies the electron relaxation time of ?-U is best, while if the elements are dissimilar, a mixed method that mixes several parameters associated with k_e from each element in the alloy is best. The introduction of all alloying elements decreases k_e; however, in binary compounds, Pu and Zr have different effects. Pu generally flattens the electronic bands but compensates for this deleterious effect by increasing electron density near the Fermi level. Zr flattens the electronic bands more severely without adding electron density near the Fermi level. Therefore, Zr decreases the k_e more than Pu in binary compounds. In ternary compounds, the difference between Pu and Zr is minimal due to the phononic change from the large mass change of Zr substitution, even at 12.5 at. %. Thus, we predict that higher loadings of Pu, and potentially other actinides, can be added to U-Pu-Zr compositions for faster recycling of spent fuel with without sacrificing k. We also note that these k_e calculation methods can be applied to non-fuel alloys that require k_e predictions, such as cladding, heat exchanger, and structural materials.
Uranium alloys are attractive recycled nuclear fuels because of their high thermal conductivity (𝑘) and fissile density. Limited experimental studies of the 𝑘 of U-Pu-Zr alloys in the range of 15 to 20 wt% Pu and 6 to 15 wt% Zr indicate that increasing the content of either Zr or Pu tends to lower 𝑘. However, which element has the greater effect on 𝑘, and the associated mechanisms, remains unclear. Here, in this study, the electron thermal conductivity (𝑘 𝑒 ) of U-Pu-Zr compositions are calculated using density functional theory. The electronic structure is evaluated to understand the effects of plutonium (Pu) and zirconium (Zr) substitution on the 𝑘 𝑒 of 𝛾-U. Alloys of up to 37.5 at. % Pu and 37.5 at. % Zr are examined. Two methods are applied to calculate 𝑘 𝑒 ; we find that the accuracy of each method depends on the electronic and mass similarities between the solute and solvent atoms. Specifically, when the solute atom is similar in electronic structure and mass, the more accurate method is that which employs the electron relaxation time of 𝛾-U, while if the elements are dissimilar, a mixed method that mixes several parameters associated with JNW_S3033426825100132 from each element in the alloy is best. The introduction of all alloying elements decreases 𝑘 𝑒 ; however, in binary compounds, Pu and Zr have different effects. Pu flattens the electronic bands but compensates for this deleterious effect by increasing electron density near the Fermi level. Zr flattens the electronic bands more severely without adding electron density near the Fermi level. Therefore, Zr decreases 𝑘 𝑒 more than Pu in binary compounds. In ternary compounds, the difference between Pu and Zr is minimal due to the phononic change from the large mass change of Zr substitution, even at 12.5 at. %. Thus, we predict that higher loadings of Pu, and potentially other actinides, can be added to U-Pu-Zr compositions for faster recycling of spent fuel without sacrificing 𝑘. We also note that these 𝑘 𝑒 calculation methods can be applied to non-fuel alloys that require 𝑘 𝑒 predictions, such as cladding, heat exchanger, and structural materials.
Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigensolution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization search analysis and domain decomposition. The source code for many of these algorithms is available.