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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 433 records · Page 24

Centrifugal‐driven, reduced‐dimension, planar chromatography

Abstract A fundamental problem with efficiency in capillary action driven planar chromatography results from diminishing flow rates as development proceeds, giving rise to molecular diffusion related band dispersion for most sample types. Overpressure and electrokinetic means to speed flow have been used successfully in TLC. We explore the use of centrifugal force (CF) to drive flow for reduced‐dimension planar platforms (ultra‐TLC, low micrometer features, and nano‐TLC, nanoscale features). The silicon wafer platforms have two forms of continuous 2D arrays created by either photolithography or metal dewetting followed by deep reactive ion etching and coated with porous SiO 2 . The flow pattern is unusual with co‐planar flows above and within the arrays. The effects of parameters such as spin rate, solvent type, and surface character on flow rates is established and can be substantially greater than capillary action flow. Using fluorescent dyes, we investigate retardation factors and chromatographic plate height; the latter falls in the low to sub‐micrometer range. To the best of our knowledge, we demonstrate the first analytical separations performed in pillar arrays using CF to augment solvent flow.

Strickhouser, Rachel B.↗

Competing Grain Boundary and Interior Deformation Mechanisms with Varying Sizes

In typical coarse-grained alloys, the dominant plastic deformations are dislocation gliding or climbing, and material strengths can be tuned by dislocation interactions with grain boundaries, precipitates, solid solutions, and other defects. With the reduction of grain size, the increase of material strengths follows the classic Hall-Petch relationship up to nano-grained materials. Even at room temperatures, nano-grained materials exhibit strength softening, or called the inverse Hall-Petch effect, as grain boundary processes take over as the dominant deformation mechanisms. On the other hand, at elevated temperatures, grain boundary processes compete with grain interior deformation mechanisms over a wide range of the applied stress and grain sizes. This book chapter reviews and compares the rate equation model and the microstructure-based finite element simulations. The latter explicitly accounts for the grain boundary sliding, grain boundary diffusion and migration, as well as the grain interior dislocation creep. Therefore the explicit finite element method has clear advantages in problems where microstructural heterogeneities play a critical role, such as in the gradient microstructure in shot peening or weldment. Furthermore, combined with the Hall-Petch effect and its breakdown, the above competing processes help construct deformation mechanism maps by extending from the classic Frost-Ashby type to the ones with the dependence of grain size.

Zhang, Wei↗

Generative modeling enables molecular structure retrieval from Coulomb explosion imaging

Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essential prerequisite for understanding and ultimately controlling femtochemistry. A key approach to tackle this challenging task is Coulomb explosion imaging, which benefited decisively from recently emerging high-repetition-rate X-ray free-electron laser sources. With this technique, information on the molecular structure is inferred from the momentum distributions of the ions produced by the rapid Coulomb explosion of molecules. Retrieving molecular structures from these distributions poses a highly non-linear inverse problem that remains unsolved for molecules consisting of more than a few atoms. Here, we address this challenge using a diffusion-based Transformer neural network. We show that the network reconstructs unknown molecular geometries from ion-momentum distributions with a mean absolute error below one Bohr radius, which is half the length of a typical chemical bond.

Artificial Intelligence (cs.AI)↗

Consistent Second Moment Methods with Scalable Linear Solvers for Radiation Transport

Second moment methods (SMMs) are developed that are consistent with the discontinuous Galerkin spatial discretization of the discrete ordinates (or S\(_N\)) transport equations. The low-order (LO) diffusion system of equations is discretized with fully consistent P\(_1\), local discontinuous Galerkin (LDG), and interior penalty (IP) methods. A discrete residual approach is used to derive SMM correction terms that make each of the LO systems consistent with the high-order discretization. We show that the consistent methods are more accurate and have better solution quality than independently discretized LO systems, that they preserve the diffusion limit, and that the LDG and IP consistent SMMs can be scalably solved in parallel on a challenging, multimaterial benchmark problem.

97 MATHEMATICS AND COMPUTING↗

A high-order finite difference method for moving immersed domain boundaries and material interfaces

Here, we present a high-order sharp treatment of immersed moving domain boundaries and material interfaces, and apply it to the advection-diffusion equation in two and three dimensions. The spatial discretization combines dimension-split finite difference schemes with an immersed boundary treatment based on a weighted least-squares reconstruction of the solution, providing stable discretizations with up to sixth order accuracy for diffusion terms and third order accuracy for advection terms. The temporal discretization relies on a novel strategy for maintaining high-order temporal accuracy in problems with moving boundaries that minimizes implementation complexity and allows arbitrary explicit or diagonally-implicit Runge-Kutta schemes. The approach is broadly compatible with popular PDE-specialized Runge-Kutta time integrators, including low-storage, strong stability preserving, and diagonally implicit schemes. Through numerical experiments we demonstrate that the full discretization maintains high-order spatial and temporal accuracy in the presence of complex 3D geometries and for a range of boundary conditions, including Dirichlet, Neumann, and flux conditions with large jumps in coefficients.

97 MATHEMATICS AND COMPUTING↗

A Review of Local-to-Nonlocal Coupling Methods in Nonlocal Diffusion and Nonlocal Mechanics

Local-to-nonlocal (LtN) coupling refers to a class of methods aimed at combining nonlocal and local modeling descriptions of a given system into a unified coupled representation. This allows to consolidate the accuracy of nonlocal models with the computational expediency of their local counterparts, while often simultaneously removing nonlocal modeling issues such as surface effects. The number and variety of proposed LtN coupling approaches have significantly grown in recent years, yet the field of LtN coupling continues to grow and still has open challenges. This review provides an overview of the state of the art of LtN coupling in the context of nonlocal diffusion and nonlocal mechanics, specifically peridynamics. Furthermore, we present a classification of LtN coupling methods and discuss common features and challenges. The goal of this review is not to provide a preferred way to address LtN coupling but to present a broad perspective of the field, which would serve as guidance for practitioners in the selection of appropriate LtN coupling methods based on the characteristics and needs of the problem under consideration.

97 MATHEMATICS AND COMPUTING↗

Toward a systematic improvement of the fixed-node approximation in diffusion Monte Carlo for solids—A case study in diamond

While Diffusion Monte Carlo (DMC) is in principle an exact stochastic method for ab initio electronic structure calculations, in practice, the fermionic sign problem necessitates the use of the fixed-node approximation and trial wavefunctions with approximate nodes (or zeros). This approximation introduces a variational error in the energy that potentially can be tested and systematically improved. Here, we present a computational method that produces trial wavefunctions with systematically improvable nodes for DMC calculations of periodic solids. These trial wavefunctions are efficiently generated with the configuration interaction using a perturbative selection made iteratively (CIPSI) method. A simple protocol in which both exact and approximate results for finite supercells are used to extrapolate to the thermodynamic limit is introduced. This approach is illustrated in the case of the carbon diamond using Slater–Jastrow trial wavefunctions including up to one million Slater determinants. Fixed-node DMC energies obtained with such large expansions are much improved, and the fixed-node error is found to decrease monotonically and smoothly as a function of the number of determinants in the trial wavefunction, a property opening the way to a better control of this error. The cohesive energy extrapolated to the thermodynamic limit is in close agreement with the estimated experimental value. Interestingly, this is also the case at the single-determinant level, thus, indicating a very good error cancellation in carbon diamond between the bulk and atomic total fixed-node energies when using single-determinant nodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two dimensional topology optimization of heat exchangers with the volume fraction method

We perform a comparison study of two topology optimizations methods applied to the design of a two fluids heat exchanger modeled with a coupled thermal-flow problem. The flow follows an isothermal and incompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion equation without internal generation and high Peclet number. To keep the two fluid phases separated, we solve two Stokes-Brinkman equations, where the Brinkman term models the other phase as a solid. These two velocity fields are then fed to the heat transfer equation. Our goal is to maximize the enthalpy at the cold outlet while constraining the pressure drop. We first solve the design modeling the solid and fluid phases with a volume fraction variable. A SIMP-like penalization in the Brinkman term drives the optimization to a discrete design. The cost and constraint function derivatives are calculated with the library pyadjoint and the optimization is performed by IPOPT. We present optimized designs in two dimensions and discuss the influence of the parameters.

Beck, VictorA.↗

Shock Dynamics in Stellar Outbursts. I. Shock Formation

Wave-driven outflows and non-disruptive explosions have been implicated in pre-supernova outbursts, supernova impostors, luminous blue variable eruptions, and some narrow-line and superluminous supernovae. To model these events, we investigate the dynamics of stars set in motion by strong acoustic pulses and wave trains, focusing on nonlinear wave propagation, shock formation, and an early phase of the development of a weak shock. We identify the shock formation radius, showing that a heuristic estimate based on crossing characteristics matches an exact expansion around the wave front and verifying both with numerical experiments. Our general analytical condition for shock formation applies to one-dimensional motions within any static environment, including both eruptions and implosions. We also consider the early phase of shock energy dissipation. We find that waves of super-Eddington acoustic luminosity always create shocks, rather than damping by radiative diffusion. Therefore, shock formation is integral to super-Eddington outbursts.

79 ASTRONOMY AND ASTROPHYSICS↗

On the Effects of Pickup Ion-driven Waves on the Diffusion Tensor of Low-energy Electrons in the Heliosphere

The effects of Alfvén cyclotron waves generated due to the formation in the outer heliosphere of pickup ions on the transport coefficients of low-energy electrons is investigated here. To this end, parallel mean free path (MFP) expressions are derived from quasilinear theory, employing the damping model of dynamical turbulence. These are then used as inputs for existing expressions for the perpendicular MFP and turbulence-reduced drift coefficient. Using outputs generated by a two-component turbulence transport model, the resulting diffusion coefficients are compared with those derived using a more typically assumed turbulence spectral form, which neglects the effects of pickup ion-generated waves. It is found that the inclusion of pickup ion effects greatly leads to considerable reductions in the parallel and perpendicular MFPs of 1–10 MeV electrons beyond ∼10 au, which are argued to have significant consequences for studies of the transport of these particles.

79 ASTRONOMY AND ASTROPHYSICS↗

GraMeR: Gra ph Me ta R einforcement learning for multi-objective influence maximization

Influence maximization (IM) is a combinatorial problem of identifying a subset of seed nodes in a network (graph), which when activated, provide a maximal spread of influence in the network for a given diffusion model and a budget for seed set size. IM has numerous applications such as viral marketing, epidemic control, sensor placement and other network-related tasks. However, its practical uses are limited due to the computational complexity of current algorithms. Recently, deep reinforcement learning has been leveraged to solve IM in order to ease the computational burden. However, there are serious limitations in current approaches, including narrow IM formulation that only consider influence via spread and ignore self-activation, low scalability to large graphs, and lack of generalizability across graph families leading to a large running time for every test network. In this work, we address these limitations through a unique approach that involves: (1) Formulating a generic IM problem as a Markov decision process that handles both intrinsic and influence activations; (2)incorporating generalizability via meta-learning across graph families. There are previous works that combine deep reinforcement learning with graph neural network, but this work solves a more realistic IM problem and incorporates generalizability across graphs via meta reinforcement learning. Extensive experiments are carried out in various standard networks to validate performance of the proposed Graph Meta Reinforcement learning (GraMeR) framework. Finally, the results indicate that GraMeR is multiple orders faster and generic than conventional approaches when applied on small to medium scale graphs.

97 MATHEMATICS AND COMPUTING↗

Partitioned exponential methods for coupled multiphysics systems

Multiphysics problems involving two or more coupled physical phenomena are ubiquitous in science and engineering. This work develops a new partitioned exponential approach for the time integration of multiphysics problems. After a possible semi-discretization in space, the class of problems under consideration is modeled by a system of ordinary differential equations where the right-hand side is a summation of two component functions, each corresponding to a given set of physical processes. The partitioned-exponential methods proposed herein evolve each component of the system via an exponential integrator, and information between partitions is exchanged via coupling terms. Here, the traditional approach to constructing exponential methods, based on the variation-of-constants formula, is not directly applicable to partitioned systems. Rather, our approach to developing new partitioned-exponential families is based on a general-structure additive formulation of the schemes. Two method formulations are considered, one based on a linear-nonlinear splitting of the right hand component functions, and another based on approximate Jacobians. The paper develops classical (non-stiff) order conditions theory for partitioned exponential schemes based on particular families of T-trees and B-series theory. Several practical methods of third order are constructed that extend the Rosenbrock-type and EPIRK families of exponential integrators. Several implementation optimizations specific to the application of these methods to reaction-diffusion systems are also discussed. Numerical experiments reveal that the new partitioned-exponential methods can perform better than traditional unpartitioned exponential methods on some problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A sensitive search for unknown spectral emission lines in the diffuse X-ray background with XMM-Newton

The Standard Model of particle physics can be extended to include sterile (right-handed) neutrinos or axions to solve the dark matter problem. Depending upon the mixing angle between active and sterile neutrinos, the latter have the possibility to decay into monoenergetic active neutrinos and photons in the keV-range while axions can couple to two photons. We have used data taken with the X-ray telescope XMM-Newton for the search of line emissions. We used pointings with high exposures and expected dark matter column densities with respect to the dark matter halo of the Milky Way. The posterior predictive p-value analysis has been applied to locate parameter space regions which favour additional emission lines. In addition, upper limits of the parameter space of the models have been generated such that the preexisting limits have been significantly improved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Many-body electronic structure of LaScO 3 by real-space quantum Monte Carlo

We present real space quantum Monte Carlo (QMC) calculations of the scandate LaSc0 3 that proved to be challenging for traditional electronic structure approaches due to strong correlation effects resulting in inaccurate band gaps from DFT and GW methods when compared with existing experimental data. Besides calculating an accurate QMC band gap corrected for supercell size biases and in agreement with numerous experiments, we also predict the cohesive energy of the crystal using the standard fixed-node QMC without any empirical or non-variational parameters. We show that promotion (optical) gap and fundamental gap agree with each other illustrating a clear absence of significant excitonic effects in the ideal crystal. We obtained these results in perfect consistency in two independent tracks that employ different basis sets (plane wave vs. localized gaussians), different codes for generating orbitals (QUANTUM ESPRESSO vs. CRYSTAL), different QMC codes (QMCPACK vs. QWALK) and different high-accuracy pseudopotentials (ccECPs vs. Troullier-Martins) presenting the maturity and consistency of QMC methodology and tools for studies of strongly correlated problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Composite Boson Description of a Low-Density Gas of Excitons

Ground-state properties of a fermionic Coulomb gas are calculated using the fixed-node diffusion Monte Carlo method. The validity of the composite boson description is tested for different densities. We extract the exciton–exciton s-wave scattering length by solving the four-body problem in a harmonic trap and mapping the energy to that of two trapped bosons. The equation of state is consistent with the Bogoliubov theory for composite bosons interacting with the obtained s-wave scattering length. The perturbative expansion at low density has contributions physically coming from (a) exciton binding energy, (b) mean-field Gross–Pitaevskii interaction between excitons, and (c) quantum depletion of the excitonic condensate (Lee–Huang–Yang terms for composite bosons). In addition, for low densities we find a good agreement with the Bogoliubov bosonic theory for the condensate fraction of excitons. The equation of state in the opposite limit of large density is found to be well described by the perturbative theory including (a) mixture of two ideal Fermi gases and (b) exchange energy. We find that for low densities both energetic and coherent properties are correctly described by the picture of composite bosons (excitons).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analytical closure to the spatially-filtered Euler equations for shock-dominated flows

To ensure numerical stability in the vicinity of shocks, a variety of methods have been used, including shock-capturing schemes such as weighted essentially non-oscillatory schemes, as well as the addition of artificial diffusivities to the governing equations. Centered finite difference schemes are often avoided near discontinuities due to the tendency for significant oscillations. However, such schemes have desirable conservation properties compared to many shock-capturing schemes. The objective of this work is to derive all necessary viscous/diffusion terms from first principles and then demonstrate the performance of these analytical terms within a centered differencing framework. The physical Euler equations are spatially-filtered with a Gaussian-like filter. Sub-filter scale (SFS) terms arise in the momentum and energy equations. Analytical closure is provided for each of them by leveraging the jump conditions for a shock. No SFS terms are present in the continuity or species equations. Here, this approach is tested for several problems involving shocks in one and two dimensions. Implemented within a centered difference code, the SFS terms perform well for a range of flow conditions without introducing excessive diffusion.

97 MATHEMATICS AND COMPUTING↗

Comparison of vapour pressure osmometry, freezing point osmometry and direct membrane osmometry for determining the osmotic pressure of concentrated solutions

Osmometry is the analytical method of measuring osmotic pressure ($π$) and related colligative properties. Accurately measuring $π$ is essential for applications that use osmosis, including drug delivery systems and water filtration methods such as forward osmosis. The three most common forms of directly or indirectly measuring $π$ are vapour pressure osmometry (VPO), freezing point osmometry (FPO), and direct membrane osmometry (DMO). In this report, the performance of VPO, FPO, and DMO are compared for various aqueous solutions, including small molecule and polymer solutes, and potentially more difficult samples such as concentrated, carbonated, or viscous solutions. Furthermore, potential problems with each of the three methods are examined. Good practices can avoid inaccuracies in DMO due to external concentration polarization and solute diffusion through the membrane. Similarly, it is important to be aware of and avoid weaknesses in VPO and FPO in order to obtain reliable results. Even with care, however, the three methods still give different values of $π$ for concentrated aqueous solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Custom-designed heat treatment simultaneously resolves multiple challenges facing 3D-printed single-crystal superalloys

Single-crystal Ni-based superalloys are currently the material of choice for turbine blade applications, especially with the emerging additive manufacturing (AM) that facilitates the manufacture/repair of these single crystals. This promising AM route, however, comes with a dilemma: in the fusion and heat affected zones after e-beam or laser induced melting, one needs a solutionizing annealing to relieve the residual stresses and homogenize the chemical/microstructure. The super-solvus solutionizing temperature is usually adopted from the protocol for the cast superalloys, which almost always causes recrystallization and stray grain growth, resulting in a polycrystalline microstructure and degrading the high-temperature mechanical performance. Here, in this paper, we demonstrate a custom-designed post-printing heat treatment to replace the conventional super-solvus one. The recovery and relatively low temperature diminish the driving force for recrystallization and the movement of stray grain boundaries, without suffocating the chemical/microstructural homogenization thanks to the narrow dendrite width and short element segregation distance. The optimal duration of the heat treatment is proposed to achieve atomic-diffusion mediated chemical homogenization while limiting γ'-particle coarsening in the interdendritic regions. Our strategy makes it practically feasible to resolve several bottleneck problems with one processing/treatment, removing a seemingly formidable obstacle to effective additive manufacturing of superalloy single crystal products.

36 MATERIALS SCIENCE↗