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At least 451 records · Page 25

Lattice-scale variations in viscosity are correlated with solution structure at mineral-water interfaces

At solid-liquid interfaces, the viscosity increases markedly from the bulk due to the collective interactions of ions and water molecules, influencing phenomena relevant to nanofluidics, colloidal dynamics, and electrochemistry. Here, in this study, we investigated dissipative forces at the boehmite-water interface using 3D atomic force microscopy. We observed an increase in interfacial solution viscosity, η, by 10-100-fold as the nanoprobe approached the surface in normal direction, with up to four oscillatory features showing average peaks of η/η bulk = 44-71. Moreover, the viscosity showed sub-nanometer variations within 0.5 nm from the interface, templated by the underlying crystal lattice and correlated with the interfacial solution structure. Beyond a near-wall region of approximately 1.2 nm, the dissipative response was comparable to that in bulk solution. Molecular dynamics simulations, along with statistical mechanical analyses, provided details on hydrodynamic structures near the interface. Specifically, the lattice-dependent dissipative responses are correlated with extensive hydrogen bonding by interfacial water molecules, which increased friction, particularly along the [001] direction. These results demonstrate how solution viscosity at mineral-water interfaces is anisotropic and correlated with the local solution structure, providing insights into the dynamics of nanocrystal attachment.

Viscosity↗

A linearity preserving nodal variation limiting algorithm for continuous Galerkin discretization of ideal MHD equations

A stabilized continuous Galerkin (CG) method for magnetohydrodynamics (MHD) is presented herein. Ideal, compressible inviscid MHD equations are discretized in space on unstructured meshes using piecewise linear or bilinear finite element bases to get a semi-discrete scheme. Stabilization is then introduced to the semi-discrete method in a strategy that follows the algebraic flux correction paradigm. This involves adding some artificial diffusion to the high order, semi-discrete method and mass lumping in the time derivative term. The result is a low order method that provides local extremum diminishing properties for hyperbolic systems. The difference between the low order method and the high order method is scaled element-wise using a limiter and added to the low order scheme. The limiter is solution dependent and computed via an iterative linearity preserving nodal variation limiting strategy. The stabilization also involves an optional consistent background high order dissipation that reduces phase errors. The resulting stabilized scheme is a semi-discrete method that can be applied to inviscid shock MHD problems and may be even extended to resistive and viscous MHD problems. To satisfy the divergence free constraint of the MHD equations, we add parabolic divergence cleaning to the system. Various time integration methods can be used to discretize the scheme in time. We demonstrate the robustness of the scheme by solving several shock MHD problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗

Sensitivity of additively manufactured AA7075 to variation in feedstock composition and print parameters

Here we developed a combined finite element and CALPHAD based model of the Laser Powder Bed Fusion (LPBF) process for AA7075 alloy that considers the effect of feedstock composition and print parameters. A single-pass of a laser on a layer of AA7075 alloy powder has been considered. Sensitivity of temperature evolution and melt pool geometry to variation in the stoichiometry of the feedstock powder and laser source characteristics have been studied. Our results indicate that deviation (up to 10%) of the feedstock composition from the AA7075 raises the maximum temperature and increases melt pool size. Excess Cu content shows the largest melt pool width and depth among all the cases. The peak temperature is higher than the standard feedstock composition in all cases, except when the Cu concentration is reduced. Increasing the scan power also results in a higher peak temperature and a larger melt pool size. Furthermore, the temperature's rise time increases by lowering the scan speed.

42 ENGINEERING↗

Strain rate sensitivity, microstructure variations, and stress-assisted β → α" phase transformation investigation on the mechanical behavior of dual-phase titanium alloys

In this study, the microstructures of three widely used dual-phase titanium alloys: Ti-6Al-4V, Ti-6Al-2Sn-4Zr-2Mo, and Ti-6Al-2Sn-4Zr-6Mo are characterized using backscatter electron imaging and the deformation behaviors in their individual α and β phases are investigated using in situ high-energy X-ray diffraction during uniaxial tension experiments. This is accompanied by calculation of the strain rate sensitivity (SRS) in these alloys, as a function of applied loading. The results of the calculated SRS and the mechanical response (in terms of lattice strains and hardening behaviors) are rationalized based on the local microstructure, composition, and texture of the alloy. A stress-induced β (BCC) to α" (orthorhombic) phase transformation is observed during the in-situ diffraction experiment, which permitted analysis of the lattice strain evolution during the phase transformation. Results from this study provide insights into the relationship between microstructure, composition, applied loading, and the deformation behavior, including effects on loading with time holds. Specifically, the results show that the microstructure, and not necessarily the chemical composition (Mo content), along with the applied loading have a dominant role in the observed SRS variation in titanium alloys. Further, the evolution of the α" (orthorhombic) phase is observed for the first time during deformation of an industrially relevant titanium alloy, Ti-6246.

36 MATERIALS SCIENCE↗

Elucidating microstructural evolution and hardness variation across friction self-piercing riveted Al-7055 using synchrotron X-ray scattering and advanced microscopy techniques

Friction self-piercing riveting (FSPR) is a unique hybrid joining technique that combines the advantages of mechanical interlocking, frictional heat, and solid-state joining (if metallurgically compatible) to produce crack free joints in high strength and/or low-ductility alloys at room temperature. Here, in the current study, Al-7055 sheets were joined using FSPR for lightweight automotive applications and significant microhardness variations were observed across the joint cross-section. A detailed microstructural characterization at multiple length scales was carried out using advanced electron microscopy and X-ray scattering techniques to provide a fundamental understanding of the process-structure-property relationships. The relative contributions of microstructural characteristics at various length scales (i.e., grain size, dislocation density, solute concentration, precipitate nature) to strengthening were estimated using existent formulations (i.e., Hall-Petch, Taylor, precipitate bypass/shear equations) and correlated to the observed microhardness values across different regions. Small-angle X-ray scattering and scanning transmission electron microscopy revealed significant changes in the size and volume fraction of precipitate species, i.e., GP-I Zones, η′, and Mg/Zn solute co-clusters, depending on the process region. It was observed that the dissolution of the small η′/GP-I zones (T ∼ 150–200 °C) in the heat-affected zone were the key reason for the hardness drop. Further, it was shown that solid-solution, dislocation, grain size and solute co-cluster strengthening played a key role in the thermo-mechanically affected zone and grain-refined zone (GRZ). Finally, these observations were leveraged along with the Zener-Holloman relationship and grain size in the GRZ to estimate the peak joining temperature of the GRZ (∼ 350 °C) near the steel rivet.

aluminum 7xxx alloy↗

Tensile behavior of diffusion bonded AA6061 - AA6061 with variation in cooling method

Hot isostatically pressed AA6061 cladding is an important structural component of the high performance, Zr-laminated U-10Mo monolithic fuel system for the application in research and test reactors. In this study, the mechanical behavior of two diffusion bonded aluminum alloy, AA6061, was examined using tensile testing. Solid-to-solid diffusion bonding between two pieces of AA6061 was performed by isothermal annealing at 560 °C for 1.5 h, and diffusion couples were subsequently cooled via three different cooling methods: furnace cooling, air cooling, and water quenching. Dog-bone shaped tensile specimens, with 10 mm in gauge length (with diffusion bonded interface in the middle), and 1.5 × 1.5 mm 2 gauge cross-sections, were fabricated from the diffusion bonded AA6061 by electro-discharge machining. Yield strength (% EL at failure) of furnace cooled, air cooled and water quenched tensile specimens determined was 82 ~ 89 MPa (10 ~ 30%), 112 ~ 116 MPa (10 ~ 14%), and 149 ~ 164 MPa (10 ~ 17%), respectively. This variation in mechanical behavior was examined with cooling-rate dependent, concentrated precipitation of Mg 2 Si at the diffusion bonded interface, with due respect for mechanical properties of the AA6061 alloy that inherently vary as a function of cooling rate from 560 °C. Finite element analysis using ABAQUS was employed to augment experimental findings with the appropriate microstructural constituents and alloy properties. Results suggest that the strength is dominated by matrix/bulk properties of AA6061, while ductility is strongly influenced by the cooling method dependent presence of Mg 2 Si precipitates at the interface.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Plastic scintillators stable for operating in wide ranges of humidity and temperature variations

To provide efficient and reproducible response to nuclear radiation, scintillating plastics should be prepared as materials of high optical transparency and homogeneity that should remain intact during the lifetime of their operation. A problem with traditionally used polyvinyltoluene (PVT) or polystyrene (PS) plastic scintillators arises from their exposure to repeated large temperature swings that cause surface and volume defects, resulting in decreased sensitivity of the detection properties. We find that the problem can be avoided by composition modifications that enable preparation of plastics with properties that are resistant to the continuous variations in environmental conditions. This paper describes improvements in physical properties that can be achieved by the addition of crosslinkers (such as divinylbenzene, DVB) and oxygen-containing compounds or copolymers (e.g. polymethylamethacrylate, PMMA) to the traditional PVT or PS polymer matrices. Results of characterization show that the new materials can be prepared with the scintillation performance equal to that of commercial plastic scintillators, such as EJ-200.

36 MATERIALS SCIENCE↗

2-D soil zymography: Accounting for the spatial variation of pH

Soil zymography is commonly used to quantify spatial distribution of hydrolytic enzyme activities on soil and plant root surfaces. It is recommended to adjust pH in zymography substrates and calibration solutions with respect to soil/root pH. However, pH values may vary greatly within a few mm of plant rhizosphere, potentially altering the distribution of pH in zymography membranes. Despite the fact that the effect of pH on the calibration of zymography membranes is generally known, its potential impact on zymography results is unaccounted for in processing zymography images and calculations of enzyme activity. In this study we assessed the effect of pH variations on the persistency of the methylumbelliferone (MUF) calibration. The studied pH values ranged from 4.5 to 7.5. The MUF calibration curves greatly deviated from that at a reference pH of 6.5, with a marked nonlinear increase of deviation with greater membrane brightness. We suggest that the problem can be partially alleviated by reducing the membrane incubation time. However, such deviations suggest the need for a more comprehensive resolution via mapping pH and using pH-specific calibrations to process zymography images. Here, we developed a MATLAB code to implement a pixel-based correction of enzyme activity for pH in processing time-lapse zymography images.

59 BASIC BIOLOGICAL SCIENCES↗

Aerosol iron speciation and seasonal variation of iron oxidation state over the western Antarctic Peninsula

The iron (Fe) speciation and oxidation state have been considered critical factors affecting Fe solubility in the atmosphere and bioavailability in the surface ocean. In this study, elemental composition and Fe speciation in aerosol samples collected at the Palmer Station in the West Antarctic Peninsula were determined using synchrotron-based X-ray fluorescence (XRF) and X-ray Absorption Near-Edge Structure (XANES) spectroscopy. The elemental composition of coarse-mode (>1 mu m) Fe-containing particles suggests that the region's crustal emission is the primary source of aerosol Fe. The Fe minerals in these aerosol particles were predominantly hematite and biotite, but minor fractions of pyrite and ilmenite were observed as well. The Fe oxidation state showed an evident seasonal variation. Further, the Fe(II) content accounted for 71% of the total Fe in the austral summer, while this fraction dropped to 60% in the austral winter. Multivariate linear models involving meteorological parameters suggested that the wind speed, relative humidity, and solar irradiance were the factors that significantly controlled the percentage of Fe(II) in the austral summer. On the contrary, no relationship was found between these factors and the Fe(II) percentage in the austral winter, suggesting that atmospheric photoreduction and regional dust emission were limited. Moreover, the snow depth was significantly (p < 0.05) correlated with the aerosol Fe concentration, confirming the limiting effect of snow/ice cover on the regional dust emission. Given that the Antarctic Peninsula has experienced rapid warming during recent decades, the ice-free areas in the Antarctic Peninsula may act as potential dust sources.

54 ENVIRONMENTAL SCIENCES↗

Coupled hydro-thermal flow and radionuclide transport driven by spatial variation of heat-generating radioactive wastes in shale formations

Deep geologic disposal of multiple nuclear waste packages with various heat sources can induce nonuniform hydro-thermal behaviors in the near-field of the repository, consequently influencing the long-term radionuclide transport in the far-field once waste form breach initiates. Here, this study looks into three cases with variation in the spatial order of six groups of heat sources (10th, 50th, 75th, 90th, 95th, and 99th percentiles of heat outputs generated from 1,981 as-loaded dual-purpose canisters in the field site) in a shale-hosted repository with respect to the uni-directional groundwater flow (from west to east): (1) cooler waste packages from west to east, (2) hotter waste packages from west to east, and (3) hottest waste packages in the middle of the repository. Our field-scale PFLOTRAN simulation represents heat-driven multiphysics coupled mechanisms, including multiphase flow, heat transfer, and chemical/radioactive transport, and also, calculates the onset of waste form breach based on temperature-dependent canister vitality. The results from this sensitivity study will quantify the short- (less than 1 × 10 3 years) and long-term (up to 1 × 10 6 years) impacts of sporadic heat pulses from waste package on the spatio-temporal perturbation in hydro-thermal flow quantities and the rate of radionuclide transport in both near- and far-field of the repository system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Imaging local luminescence variations in CdSe 0.1 Te 0.9 thin films grown by the colossal grain growth process

Clear visualization and understanding of luminescence properties of grain interiors and grain boundaries in polycrystalline thin-film photovoltaic materials are crucial to achieving high-performance solar cells. Luminescence-based measurements, for example, reveal sub-bandgap energetic disorder or impurity-related radiative transitions in these materials, and when performed in the absolute scale, they can show the extent of voltage-limiting non-radiative recombination. Here we use a hyperspectral imaging technique to investigate inter- and intra-grain photoluminescence variations in polycrystalline CdSe 0.1 Te 0.9 films made by the colossal grain growth process. We observe that grain boundaries show higher luminescence than grain interiors for all energies below the bandgap energy. Multiple distinct sub-bandgap defect transitions are detected and determined to be related to donor-acceptor pair impurities. A comparison of the excitation-intensity-dependent photoluminescence at the grain boundaries with grain interiors suggests that carrier concentration is higher at grain boundaries. This finding is supported by photoemission electron microscopy imaging of the films, showing approximately 70 meV upward energy shift in the band structure at the grain boundaries. Finally, we investigate a dramatic thermal quenching behavior related to the donor-acceptor pairs luminescence over a temperature range and use a rate-equation model to attribute it to the sudden redirection of the radiative recombination channels to non-radiative channels with increasing temperature.

14 SOLAR ENERGY↗

Laser Wakefield Accelerator modelling with Variational Neural Networks

A machine learning model was created to predict the electron spectrum generated by a GeV-class laser wakefield accelerator. The model was constructed from variational convolutional neural networks, which mapped the results of secondary laser and plasma diagnostics to the generated electron spectrum. An ensemble of trained networks was used to predict the electron spectrum and to provide an estimation of the uncertainty of that prediction. It is anticipated that this approach will be useful for inferring the electron spectrum prior to undergoing any process that can alter or destroy the beam. In addition, the model provides insight into the scaling of electron beam properties due to stochastic fluctuations in the laser energy and plasma electron density.

43 PARTICLE ACCELERATORS↗

Sedimentation and shear-induced dynamics of spheroids in fluids with spatial viscosity variations

A generalized reciprocal theorem is used to relate the force and torque induced on a particle in an inertia-less fluid with small variation in viscosity to integrals involving Stokes flow fields and the spatial dependence of viscosity. These resistivity expressions are analytically evaluated using spheroidal harmonics and then used to obtain the mobility of the spheroid during sedimentation, and in linear flows, of a fluid with linear viscosity stratification. The coupling between the rotational and translational motion induced by stratification rotates the spheroid’s centerline, creating a variety of rotational and translational dynamics dependent upon the particle’s aspect ratio, κ, and the component of the stratification unit vector in the gravity direction, d g . Spheroids with 0.55 ⪅ κ ⪅ 2.0 exhibit the largest variety of settling behaviors. Interestingly, this range covers most microplastics and typical microorganisms. One of the modes include a stable orientation dependent only on κ and d g , but independent of initial orientation, thus allowing for the potential control of settling angles and sedimentation rates. In a simple shear flow, cross-streamline migration occurs due to the stratification-induced force generated on the particle. Similarly, a particle no longer stays at the stagnation point of a uniaxial extensional flow. While fully analytical results are obtained for spheroids, numerical simulations provide a source of validation. These simulations also provide additional insights into the stratification-induced force- and torque-producing mechanisms through the stratification-induced stress, which is not accessed in the reciprocal theorem-based analytical calculations.

Geophysical and Geological Flows: Stratified flows↗

Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders

We report the design/discovery of new materials is highly nontrivial owing to the near-infinite possibilities of material candidates and multiple required property/performance objectives. Thus, machine learning tools are now commonly employed to virtually screen material candidates with desired properties by learning a theoretical mapping from material-to-property space, referred to as the forward problem. However, this approach is inefficient and severely constrained by the candidates that the human imagination can conceive. Thus, in this work on polymers, we tackle the materials discovery challenge by solving the inverse problem: directly generating candidates that satisfy desired property/performance objectives. We utilize syntax-directed variational autoencoders (VAE) in tandem with Gaussian process regression (GPR) models to discover polymers expected to be robust under three extreme conditions: (1) high temperatures, (2) high electric field, and (3) high temperature and high electric field, useful for critical structural, electrical, and energy storage applications. This approach to learn from and augment) human ingenuity is general and can be extended to discover polymers with other targeted properties and performance measures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Speciation and Aqueous Dissolution of Macronutrients in Fire Ash: Variation across Ecosystems and the Effects on Nutrient Cycling

This study investigated the speciation and aqueous dissolution of macronutrients in fire ash from diverse ecosystems and speciation of ash and smoke from laboratory burning, exploring the variations and their causes. The speciation of phosphorus (P), calcium (Ca), and potassium (K) in fire ash from five globally distributed ecosystems was characterized by using X-ray absorption spectroscopy and sequential fractionation. Aqueous dissolution of the macronutrients was measured by batch experiments at acidic and alkaline pHs. The results showed that P existed mainly as Ca phosphates, Ca as double carbonates, calcite, and sulfates, and most K was associated with Ca carbonates. Mineralogy and the relative abundance of the species were primarily controlled by elemental stoichiometry and fire temperature. Differences in Ca and P speciation existed between ash and smoke from laboratory burning, possibly caused by the temperature difference and/or mass fractionation during burning. The rates, extents, and pH dependencies of macronutrient dissolution differed among macronutrients and depended on their speciation, with K being highly soluble and the P and Ca regulated by solution pH. The variability in ash macronutrient chemistry and ecosystemspecific fire ash loads resulted in varying loads and availability of individual macronutrient from fire among ecosystems. This study provides a mechanistic understanding of how fires transform the chemistry of macronutrients and affect macronutrient returns to soils across different ecosystems, which is essential for evaluating the disturbance to ecosystem nutrient cycling by fires.

54 ENVIRONMENTAL SCIENCES↗

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization Stability in Excited-State-Specific Variational Monte Carlo

Here, we investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method's stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗