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At least 271 records · Page 15

The role of breakup and coalescence in fine-scale bubble-induced turbulence. I. Dynamics

We study the effect of bubble breakup and coalescence on fine-scale dynamics of bubbly turbulent flows using direct numerical simulations. We perform two different simulations of dilute bubbly flows of void fraction 0.5%: one with bubbles breaking up and coalescing and the other without these physical processes. The volume of the fluid method is used for simulating bubbles undergoing breakup and coalescence while the bubbles are treated as rigid spheres in the immersed boundary method simulation. The energy spectrum in both types of simulation, consistent with previous studies, exhibits a -3 slope. We follow a single infinitesimal fluid element as it evolves to understand velocity gradient dynamics using conditional mean trajectories. We note finite-time divergence when the fluid element evolves under the action of inertial and pressure dynamics. The inertial, pressure, and viscous velocity gradient dynamics, when considered individually, produce the same results for bubble-induced turbulence (BIT) as with the classical homogeneous isotropic turbulence (HIT). Yet when the overall velocity gradient dynamics is considered, BIT results in non-cyclic trajectories moving toward stable node and unstable saddle while classical HIT shows cyclic behavior in their trajectories that move toward the origin. Interestingly, both the volume of fluid and immersed boundary simulations produce similar results. Therefore, there are two main takeaways from this research. First, new velocity gradient models are needed for BIT as their velocity gradients behavior is entirely different from the HIT. Second, we can neglect the bubble topology, breakup, and coalescence while studying or modeling the fine-scale dynamics of BIT.

42 ENGINEERING↗

Approximating the linear response of physical chaos

Abstract Parametric derivatives of statistics are highly desired quantities in prediction, design optimization and uncertainty quantification. In the presence of chaos, the rigorous computation of these quantities is certainly possible, but mathematically complicated and computationally expensive. Based on Ruelle’s formalism, this paper shows that the sophisticated linear response algorithm can be dramatically simplified in higher-dimensional systems featuring statistical homogeneity in the physical space. We argue that the contribution of the SRB (Sinai–Ruelle–Bowen) measure gradient, which is an integral yet the most cumbersome part of the full algorithm, is negligible if the objective function is appropriately aligned with unstable manifolds. This abstract condition could potentially be satisfied by a vast family of real-world chaotic systems, regardless of the physical meaning and mathematical form of the objective function and perturbed parameter. We demonstrate several numerical examples that support these conclusions and that present the use and performance of a simplified linear response algorithm. In the numerical experiments, we consider physical models described by differential equations, including Lorenz 96 and Kuramoto–Sivashinsky.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Interpreting experimental measurements of helium bubbles using stochastic cluster dynamics models of heterogeneous nucleation and growth in irradiated ferritic alloys

Among a number of other advantageous features, ferritic/martensitic steels are being considered as fusion reactor structural materials due to their low intrinsic swelling under irradiation. However, under high-energy neutron irradiation, He produced through (n, α) reactions stabilizes vacancy clusters, which then act as seeds for bubble formation and growth, negating the intrinsic swelling resistance of these alloys. Standard models of irradiation damage accumulation and microstructural evolution consider homogeneous nucleation as the basis for bubble formation and growth. However, this generally does not explain the large bubble densities and sizes observed experimentally under a number of different conditions. Here, we propose a more realistic physical model of bubble nucleation, formation, and growth designed to capture recent experimental measurements of He-bubble formation and evolution during co-implantation of He and Fe ions in model ferritic alloys. We find that experimental results are explained only when the following three features are considered simultaneously: (i) heterogeneous nucleation of He-vacancy bubbles at defect sinks (e.g., dislocations, grain boundaries, and second-phase precipitates), (ii) nucleation and growth of bubbles via the ‘trap mutation’ mechanism (i.e., spontaneous production of Frenkel pairs due to absorption of He atoms), and (iii) transition from a growth-limited, He-stabilized bubble regime to a ‘runaway’ void-type growth scenario. The model is implemented into a stochastic cluster dynamics framework that takes advantage of cluster size grouping methods to accelerate the simulations, allowing us to reach 10 dpa of simulated irradiated dose, and to capture cluster sizes in excess of 20 nm. Further, a careful extrapolation exercise conducted assuming classical nucleation theory leads to excellent agreement with the experimental measurements at 50 dpa of irradiation.

36 MATERIALS SCIENCE↗

Dark photon dark matter in the presence of inhomogeneous structure

Dark photon dark matter will resonantly convert into visible photons when the dark photon mass is equal to the plasma frequency of the ambient medium. In cosmological contexts, this transition leads to an extremely efficient, albeit short-lived, heating of the surrounding gas. Existing work in this field has been predominantly focused on understanding the implications of these resonant transitions in the limit that the plasma frequency of the Universe can be treated as being perfectly homogeneous, \ie neglecting inhomogeneities in the electron number density. In this work we focus on the implications of heating from dark photon dark matter in the presence of inhomogeneous structure (which is particularly relevant for dark photons with masses in the range $10^{-15} \, {\rm eV} \, \lesssim m_{A^\prime} \lesssim 10^{-12}$ eV), emphasizing both the importance of inhomogeneous energy injection, as well as the sensitivity of cosmological observations to the inhomogeneities themselves. More specifically, we derive modified constraints on dark photon dark matter from the Ly-$\alpha$ forest, and show that the presence of inhomogeneities allows one to extend constraints to masses outside of the range that would be obtainable in the homogeneous limit, while only slightly relaxing their strength. We then project sensitivity for near-future cosmological surveys that are hoping to measure the 21cm transition in neutral hydrogen prior to reionization, and demonstrate that these experiments will be extremely useful in improving sensitivity to masses near $\sim 10^{-14}$ eV, potentially by several orders of magnitude. Finally, we discuss implications for reionization, early star formation, and late-time $y$-type spectral distortions, and show that probes which are inherently sensitive to the inhomogeneous state of the Universe could resolve signatures unique to the light dark photon dark matter scenario, and thus offer a fantastic potential for a positive detection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Soft integrals and soft anomalous dimensions at $\mathrm{N^3LO}$ and beyond

We calculate soft phase-space and loop master integrals for the computation of color-singlet cross sections through N 3 LO in perturbative QCD. Our results are functions of homogeneous transcendental weight and include the first nine terms in the expansion in the dimensional regulator ϵ. We discuss the application of our results to the computation of deeply-inelastic scattering and e + e - annihilation processes. We use these results to compute the perturbative coefficient functions for the Drell-Yan and gluon-fusion Higgs boson production cross sections to higher orders in ϵ through N 3 LO in QCD in the limit where only soft partons are produced on top of the colorless final state. Furthermore, we extract the anomalous dimension of the inclusive threshold soft function and of the N-Jettiness beam and jet functions to N 4 LO in perturbative QCD.

higher-order perturbative calculations↗

Labile Fe(III) supersaturation controls nucleation and properties of product phases from Fe(II)-catalyzed ferrihydrite transformation

We report Fe(II)-catalyzed ferrihydrite (Fh) transformation to more crystalline iron (oxyhydr)oxide phases is a widely occurring geochemical process which has been extensively studied as a function of Fe(II)/Fh ratios at fixed Fh loadings. However, recent isolation of an intermediate Fe(III) species resulting from Fe(II)-Fh contact that facilitates transformation by dissolution/reprecipitation suggests that the kinetics and properties of product phases will instead depend mostly on its rate of accumulation to a critical concentration, consistent with principles in the classical nucleation theory (CNT). This suggests a dependence both on the loading of Fe(II) on the surface, which controls the rate of labile Fe(III) formation, as well as the available volume of solution, which also impacts how fast it can achieve its critical concentration to nucleate product phases. To specifically examine the latter effect, here we studied transformation of 15 mg Fh in 1 mM FeSO 4 solutions at pH 7.2 in batch suspensions of 30 mL, 150 mL, and 450 mL volumes. Time-dependent concentrations of aqueous Fe(II), surface-associated Fe(II), and resulting labile Fe(III) were monitored along with bulk solids characterization as a function of time. Transmission electron microscopy (TEM) was used to visualize the evolution of phases at identical locations on TEM grids. The collective results show that the rates of Fh loss and emergence of product lepidocrocite (Lp) and goethite (Gt) as well as their phase proportions, nucleation mode and morphological properties depend directly on the rate of accumulation of the labile Fe(III) precursor to its critical concentration, which in our experiments was controlled simply by varying the available volume of solution into which it enters. Statistical analyses of TEM image data suggest that while both heterogeneous and homogeneous nucleation occurred in all experiments, the former was increasingly favored at lower Fh/solution ratio due to its lower nucleation barrier being more favorable at attendant lower supersaturations of Fe(III).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Learning turbulent flows with generative models for super resolution and sparse flow reconstruction

Neural operators are promising surrogates for dynamical systems but when trained with standard L 2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that combining operator learning with generative modeling overcomes this limitation. We consider three practical turbulent-flow challenges where conventional neural operators fail: spatio-temporal super-resolution, forecasting, and sparse flow reconstruction. For Schlieren jet super-resolution, an adversarially trained neural operator (adv-NO) reduces the energy-spectrum error by 15 × while preserving sharp gradients at neural operator-like inference cost. For 3D homogeneous isotropic turbulence, adv-NO trained on only 160 timesteps from a single trajectory forecasts accurately for five eddy-turnover times and offers 114 × wall-clock speed-up at inference than the baseline diffusion-based forecasters, enabling near-real-time rollouts. For reconstructing cylinder wake flows from highly sparse Particle Tracking Velocimetry-like inputs, a conditional generative model infers full 3D velocity and pressure fields with correct phase alignment and statistics. These advances enable accurate reconstruction and forecasting at low compute cost, bringing near-real-time analysis and control within reach in experimental and computational fluid mechanics.

Fluid dynamics↗

Molecular-Level Design of Heterogeneous Chiral Catalysts

A recent major focus of catalyst research has been on improving the selectivity or atom efficiency of catalytic processes. Perhaps the most subtle and difficult form of selectivity to control is enantioselectivity, a catalyst’s ability to preferentially yield one enantiomer of a chiral product. Since two enantiomers are identical in all respects except for their mirror reflection symmetry, both are formed in non-chiral environments at exactly equal rates; only by introducing some type of chiral modification to the system can the rate of formation of one enantiomer be favored over the other. This has been successfully achieved for homogeneous-phase, organometallic catalysts, but the empirical development of heterogeneous-phase analogs has proven elusive. The design of such heterogeneous-phase catalysts would obviate the need for inefficient purification steps to remove the heavy-metal catalysts. The goal of the proposed research by the Chiral Catalysis Group is to understand the interactions of prochiral reactants on chirally modified surfaces that lead to the preferential formation of one enantiomer over the other. There are two general concepts for designing heterogeneous-phase enantioselective catalysts. The first adopts the strategy used in homogeneous phase, by adding a chiral modifier to the surface. This approach, while conceptually simple has challenges associated with modifying an extended surface. The second concept, which is unique to extended surfaces, is the idea of creating surfaces that are themselves naturally chiral. A fundamental understanding of the interactions that control enantioselectivity will enable the Chiral Catalysis Group to develop the concepts necessary to design novel, heterogenous catalytic materials. Enantioselectivity is also central to catalytic processes that underpin the pharmaceutical and agrochemical industries. With funding from the Department of Energy, the Chiral Catalysis Group has played a leading role in developing a fundamental understanding of chiral catalysis and of the adsorbate structures, interactions and kinetic effects that control heterogenous-phase enantioselectivity. The proposed research program is organized conceptually around three types of enantiospecific interactions: interactions with naturally chiral surfaces; those with modified surfaces categorized as chirally templated surfaces; and one-to-one interactions of prochiral molecules with chiral surface modifiers. Our specific goals are to: (1) determine the structures of chiral surfaces, prochiral reactants, chiral products and chiral modifiers; (2) understand the enantiospecific interactions that occur between prochiral reactants and chiral products with chirally modified surfaces; (3) develop methods for detection of enantiospecific surface phenomena; and (4) elucidate enantioselective reaction pathways and the interactions that control them. The range of expertise within the Chiral Catalysis Group includes molecular-scale theory, surface science experiments, state-of-the-art spectroscopic, kinetic and atomic-scale imaging capabilities carried out in vacuum and under more-realistic liquid- and gas-phase environments complemented by catalytic measurements. By fully integrating such a breadth of approaches and extensive expertise, the Chiral Catalysis Group will, for the first time, be able to understand, rationally design and then control active sites for optimal enantioselectivity. In addition to having a significant impact on the field of chiral catalysis, the proposed research program will further our general understanding of the molecular-scale origins of catalytic selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning accelerated turbulence modeling of transient flashing jets

We report modeling the sudden depressurization of superheated liquids through nozzles is a challenge because the pressure drop causes rapid flash boiling of the liquid. The resulting jet usually demonstrates a wide range of structures, including ligaments and droplets, due to both mechanical and thermodynamic effects. As the simulation comprises increasingly numerous phenomena, the computational cost begins to increase. One way to moderate the additional cost is to use machine learning surrogacy for specific elements of the calculation. This study presents a machine learning-assisted computational fluid dynamics approach for simulating the atomization of flashing liquids accounting for distinct stages, from primary atomization to secondary breakup to small droplets using the Σ - Y model coupled with the homogeneous relaxation model. Notably, the models for thermodynamic non-equilibrium (HRM) and Σ - Y are coupled, for the first time, with a deep neural network that simulates the turbulence quantities, which are then used in the prediction of superheated liquid jet atomization. The data-driven component of this method is used for turbulence modeling, avoiding the solution of the two-equation turbulence model typically used for Reynolds-averaged Navier-Stokes simulations for these problems. Both the accuracy and speed of the hybrid approach are evaluated, demonstrating adequate accuracy and at least 25% faster computational fluid dynamics simulations than the traditional approach. This acceleration suggests that perhaps additional components of the calculation could be replaced for even further benefit. Published under an exclusive license by AIP Publishing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analytical benchmark solution for 1-D neutron transport coupled with thermal conduction and material expansion

In this work we present fully analytical solutions for a class of finite, homogeneous, 1-D slab benchmark problems with nonlinear temperature feedback effects. The proposed class of benchmarks include multiplicative 1-D neutron transport (limited to quasistatic S{sub 2} with μ = ±1) coupled with thermal conduction, convection, Doppler broadening, and expansion effects along the length of the slab. This class of benchmark models, along with the corresponding analytical solutions, are valuable for validating multiphysics analysis frameworks that support coupled neutronics/thermal/structural calculations. Analytical solutions for the benchmarks are obtained by introducing an ansatz that the equilibrium flux and temperature distributions in the slab have the same shape. Specific values for the total microscopic cross section, σ{sub t,0}, and conductive heat transfer coefficient, h, that satisfy the assumed ansatz are then determined. A discussion of the procedure for generating benchmark models and analytical solutions is provided, along with numerical results for an example set of model parameters and thoughts on practical applications of the benchmarks for multiphysics code validation. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Asymptotic Relaxation of Moment Equations for a Multi-species, Homogeneous BGK Model

Multi-species BGK models describe the dynamics of rarefied gases with constituent particles of different elements or compounds with potentially nontrivial velocity distributions. Here, in this paper, moment equations for the bulk velocities, energies, and temperatures of a spatially homogeneous multi-species BGK model are examined. A key challenge in analyzing these equations is the fact that the collision frequencies are allowed to depend on the species temperatures, which allows for more realistic simulations of dilute gas flow. Therefore, a positive lower bound is established for the species temperatures. With this lower bound, a global existence and uniqueness of solutions to the coupled velocity-energy ODE system is established. The lower bound also enables a proof of exponential decay to a unique steady-state solution. Numerical results are presented to demonstrate how the bulk velocities and temperatures relax for large times.

97 MATHEMATICS AND COMPUTING↗

On the effect of scalar flux weighing of linearly anisotropic scattering matrices in few-group transport calculations

The majority of the codes available for homogenized group constant generation for deterministic transport calculations apply the approximation of scalar flux weighting during energy group condensation of higher-order anisotropic scattering matrices. In this paper, we discuss the effect of scalar flux weighting of the linearly anisotropic scattering matrices in the frame of S P{sub 3} and S{sub 12} calculations performed for a two-dimensional VVER-440 reactor benchmark. To compare group constants generated for two neutron energy groups, an infinite pin cell was homogenized with Serpent 2 and ERANOS ECCO. Serpent 2 applies scalar flux, while ERANOS ECCO performs current weighting of the linearly anisotropic scattering matrices during energy group condensation. For analyzing the effect of the various weighting options, three simple reactor models were built assuming different core sizes using standard rectangular assemblies with 15*15 fuel pins. Diffusion, SP{sub 3} and S{sub 12} calculations were performed for the 3 models using group constants generated with Serpent 2 and ERANOS ECCO. The effect of scalar flux weighting of linearly anisotropic scattering matrices is shown by comparing the decrease in reactivity due to the decreased reactor size, as well as the assembly power distribution to reference results obtained with Serpent 2 Monte Carlo calculations. Neglecting higher than linearly anisotropic scattering and indirect application of diffusion coefficients in higher-order transport calculations is advised if angular flux-moment spectra weighted higher-order scattering matrices cannot be generated. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coarse-graining Hamiltonian systems using WSINDy

Abstract Weak form equation learning and surrogate modeling has proven to be computationally efficient and robust to measurement noise in a wide range of applications including ODE, PDE, and SDE discovery, as well as in coarse-graining applications, such as homogenization and mean-field descriptions of interacting particle systems. In this work we extend this coarse-graining capability to the setting of Hamiltonian dynamics which possess approximate symmetries associated with timescale separation. A smooth $$\varepsilon$$ ε -dependent Hamiltonian vector field $$X_\varepsilon$$ X ε possesses an approximate symmetry if the limiting vector field $$X_0=\lim _{\varepsilon \rightarrow 0}X_\varepsilon$$ X 0 = lim ε → 0 X ε possesses an exact symmetry. Such approximate symmetries often lead to the existence of a Hamiltonian system of reduced dimension that may be used to efficiently capture the dynamics of the symmetry-invariant dependent variables. Deriving such reduced systems, or approximating them numerically, is an ongoing challenge. We demonstrate that WSINDy can successfully identify this reduced Hamiltonian system in the presence of large perturbations imparted in the $$\varepsilon >0$$ ε > 0 regime, while remaining robust to extrinsic noise. This is significant in part due to the nontrivial means by which such systems are derived analytically. WSINDy naturally preserves the Hamiltonian structure by restricting to a trial basis of Hamiltonian vector fields. The methodology is computationally efficient, often requiring only a single trajectory to learn the global reduced Hamiltonian, and avoiding forward solves in the learning process. In this way, we argue that weak-form equation learning is particularly well-suited for Hamiltonian coarse-graining. Using nearly-periodic Hamiltonian systems as a prototypical class of systems with approximate symmetries, we show that WSINDy robustly identifies the correct leading-order system, with dimension reduced by at least two, upon observation of the relevant degrees of freedom. While our main contribution is computational, we also provide a contribution to the literature on averaging theory by proving that first-order averaging at the level of vector fields preserves Hamiltonian structure in nearly-periodic Hamiltonian systems. This provides theoretical justification for our approach as WSINDy’s computations occur at the level of Hamiltonian vector fields. We illustrate the efficacy of our proposed method using physically relevant examples, including coupled oscillator dynamics, the Hénon–Heiles system for stellar motion within a galaxy, and the dynamics of charged particles.

97 MATHEMATICS AND COMPUTING↗

Combined First-Principles and Experimental Investigation into the Reactivity of Codeposited Chromium–Carbon under Pressure

High-pressure synthesis in the diamond anvil cell suffers from the lack of a general approach for the control of precursor stoichiometry and homogeneity. Here, we present results from a new method we have developed that uses magnetron cosputtering to prepare stoichiometrically precise and atomically mixed amorphous films of Cr:C. Laser-heated diamond anvil cell experiments carried out on a flake of this sample at pressures between 13.5 and 24.3 GPa lead to the observation of Cr 3 C (Pnma) over the entire pressure range–in good agreement with our in-house theoretical predictions–but also reveal two other metastable phases that were not expected: a novel monoclinic chromium carbide phase and the NaCl-type CrC (Fm3̅m) phase. The unexpected stability of CrC is investigated by using first-principles methods, revealing a large stabilizing effect tied to substoichiometry at the carbon site. These results offer an important case study into the current limitations of crystal structure prediction methods with regard to phase complexity and bolster the growing need for advanced theoretical approaches that can more completely survey experimentally unexplored phase space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic-Scale Surface Studies of Bulk Metallic Glasses. Final Report

Bulk metallic glasses (BMGs) are of both scientific and technological interest because the absence of periodic atomic arrangements provides them with unique physical, chemical, and mechanical properties. Their high strength, superior elasticity, and an ability to be easily formed into virtually unlimited shapes with feature sizes from centimeters to Angstroms by blow molding and thermoplastic forming makes them an attractive choice for more and more practical applications and products. Due to their complex internal structure, however, experiments that yield insight into their exact atomic arrangements have been scarce. As a result, glass physics is one of the last remaining unexplored fields of materials science despite the scientific and technological importance of glasses in our daily lives, and the question how to characterize and control matter away from equilibrium, as glasses are, was listed as one of five Grand Challenges in a recent DoE report. The main reason for the slow progress in glass physics is the lack of experimental tools that enable access to atomic-scale structural and behavioral information for disordered materials. Such atomic-scale knowledge is mandatory to establish structure-property relationships that ultimately could allow to custom-design alloys featuring specific desired characteristics. With no such relationships available, theory development in glass remains basic and the few that exist are often untested. The aim of this research was to enable progress in our understanding of BMGs by developing a new approach that will allow a meaningful application of local surface science methods to specially prepared BMG samples to obtain a wealth of quantitative information on their atomic arrangements. Key was the availability of specially prepared samples whose surfaces feature large atomically flat terraces despite being entirely amorphous, which we have produced from a Pt 57.5 Cu 14.7 Ni 5.3 P 22.5 alloy (‘Pt-BMG’) both under ambient conditions as well as in ultrahigh vacuum using a unique setup that has been specially developed within this grant. Our approach starts with the in-situ preparation of oxide crystals that are terminated by large terraces, from which exact mirror images out of BMG will be produced using thermoplastic forming (TPF); for the research within this grant, we have successfully used (001)-oriented SrTiO 3 single crystal surfaces as well as (100)-, (110)-, and (111)-oriented single crystals made from LaAlO 3 . Since the resulting BMG replicas display all features of the original crystal with sub-Angstrom fidelity, thereby mimicking the original crystal’s termination by atomically flat terraces without being crystalline themselves, they are ideally suited for further investigation. The following atomic-scale local studies were then carried within this proposal: (i) high-resolution surface imaging and local spectroscopy using scanning probe microscopy, which showed disordered atom-like features and revealed changes in the gradient of the local surface potential on a 1-2 nm length scale; (ii) characterization of atomic-scale plastic flow with affected volumes as low as 1000 atoms, which showed local hardness near or above the theoretically predicted maximum and, once plastic deformation was initiated, homogeneous flow of the atoms involved; (iii) characterization of surface relaxation processes and the onset of crystallization induced by annealing, which showed that upon heating over the material’s glass transition temperature, the surface rearranges and relaxes towards a more stable, denser packed glass, which increases on-terrace surface roughness, while surface tension smoothens step edges; and (iv) studies that investigate the dependence of the material’s mechanical properties and structure on processing parameters, revealing that relaxed glasses get denser, harder, and more elastic. In combination, this information allows to combine structural models with mechanical properties and preparation history, thereby facilitating the development of preparation-structure-property relationships for metallic glasses. With the availability of such information, bulk metallic glasses can be further optimized to be used in more and more applications in industry.

36 MATERIALS SCIENCE↗

Experimental and theoretical investigation of the crystalline surface, film, and interface properties of antiperovskite Mn 3 GaN grown by molecular beam epitaxy on MgO(001)

Here, we present a study of the epitaxial growth, characterization, and theoretical modeling of thin film antiperovskite Mn 3 GaN, an antiferromagnetic material with kagome structure which is grown on MgO (001) substrates using N-plasma-assisted molecular beam epitaxy. Reflection high energy electron diffraction is used to assess the in-plane evolution of the film structure during growth, and the surface is investigated in-situ using scanning tunneling microscopy and Auger electron spectroscopy. These results are combined with precision measurements done ex-situ determining the film lattice constants using a combination of x-ray diffraction with reciprocal space mapping and scanning transmission electron microscopy. Overall, a uniform, homogeneous film with an atomically smooth vacuum surface and atomically sharp substrate interface is found having very small in-plane tensile strain and mild out-of-plane compressive strain. First-principles theoretical calculations are applied in order to ascertain the lowest energy models for both the Mn 3 GaN surface and the Mn 3 GaN/MgO film/substrate interface. Models including MnGa versus MnN surface layers and MnGa versus MnN interfacial layers are considered as functions of both the Mn and Ga chemical potentials. The predictions are discussed in comparison to the experimental results. The overall findings suggest that Mn 3 GaN on MgO(001) is a viable epitaxial film which can be further explored in connection with antiferromagnetic spintronics.

Density functional theory↗

Measuring the giant radio galaxy length distribution with the LoTSS

Many massive galaxies launch jets from the accretion disk of their central black hole, but only ~10 3 instances are known in which the associated outflows form giant radio galaxies (GRGs, or giants): luminous structures of megaparsec extent that consist of atomic nuclei, relativistic electrons, and magnetic fields. Large samples are imperative to understanding the enigmatic growth of giants, and recent systematic searches in homogeneous surveys constitute a promising development. For the first time, it is possible to perform meaningful precision statistics with GRG lengths, but a framework to do so is missing. We measured the intrinsic GRG length distribution by combining a novel statistical framework with a LOFAR Two-metre Sky Survey (LoTSS) sample of freshly discovered giants. In turn, this allowed us to answer an array of questions on giants. For example, we can now assess how rare a 5 Mpc giant is compared with one of 1 Mpc, and how much larger – given a projected length – the corresponding intrinsic length is expected to be. Notably, we can now also infer the GRG number density in the Local Universe. We assumed the intrinsic GRG length distribution to be Paretian (i.e. of power-law form) with tail index ξ, and predicted the observed distribution by modelling projection and selection effects. To infer ξ, we also systematically searched the LoTSS for hitherto unknown giants and compiled the largest catalogue of giants to date. We show that if intrinsic GRG lengths are Pareto distributed with index ξ, then projected GRG lengths are also Pareto distributed with index ξ. Selection effects induce curvature in the observed projected GRG length distribution: angular length selection flattens it towards the lower end, while surface brightness selection steepens it towards the higher end. We explicitly derived a GRG’s posterior over intrinsic lengths given its projected length, laying bare the ξ dependence. We also discovered 2060 giants within LoTSS DR2 pipeline products; our sample more than doubles the known population. Spectacular discoveries include the largest, second-largest, and fourth-largest GRG known (l p = 5.1 Mpc, l p = 5.0 Mpc, and l p = 4.8 Mpc), the largest GRG known hosted by a spiral galaxy (l p = 2.5 Mpc), and the largest secure GRG known beyond redshift 1 (l p = 3.9 Mpc). We increase the number of known giants whose angular length exceeds that of the Moon from 10 to 23; among the discoveries is the angularly largest known radio galaxy in the Northern Sky, which is also the angularly largest known GRG ($\phi$ = 2°). Combining theory and data, we determined that intrinsic GRG lengths are well described by a Pareto distribution, and measured the index ξ = –3.5 ± 0.5. This implies that, given its projected length, a GRG’s intrinsic length is expected to be just 15% larger. Finally, we determined the comoving number density of giants in the Local Universe to be n GRG = 5 ± 2(100 Mpc) –3 . We developed a practical mathematical framework that elucidates the statistics of giant radio galaxy lengths. Through a LoTSS search, we also discovered 2060 new giants. By combining both advances, we determined that intrinsic GRG lengths are well described by a Pareto distribution with index ξ = –3.5 ± 0.5, and that giants are truly rare in a cosmological sense: most clusters and filaments of the Cosmic Web are not currently home to a giant. Thus, our work yields new observational constraints for analytical models and simulations featuring radio galaxy growth.

79 ASTRONOMY AND ASTROPHYSICS↗