Peak effect due to competing vortex ground states in superconductors with large inclusions
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Willa, Roland↗
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Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing
Analysis of reactive-diffusion simulations representing complex mixing processes requires a large number of independent model runs. For each high-fidelity model simulation, the model inputs are varied and the predicted mixing behavior is represented by temporal and spatial changes in species concentration. It is then required to discern how the model inputs (such as diffusivity, dispersion, anisotropy, and velocity field properties) impact the mixing process. This task is challenging and typically involves interpretation of large model outputs representing temporal and spatial changes of species concentration within the model domain. Yet, the task can be automated and substantially simplified by applying Machine Learning (ML) methods. Here, we present an application of an unsupervised ML method (called NTF k ) using Non-negative Tensor Factorization (NTF) coupled with a custom clustering procedure based on k-means to reveal the temporal and spatial features in product concentrations. An attractive and unique aspect of the proposed ML method is that it ensures the extracted features are non-negative, which is important to obtain a meaningful deconstruction of the mixing processes. The ML methodology is applied to a large set of high-resolution finite-element model simulations representing anisotropic reaction-diffusion processes in perturbed vortex-based velocity fields. The applied finite-element method ensures that spatial and temporal species concentration are always non-negative, even in the case of high anisotropic contrasts. The simulated reaction is a fast irreversible bimolecular reaction A+B→C , where species A and B react to form species C. The reactive-diffusion model input parameters that control mixing include properties of the velocity field (such as vortex structures), anisotropic dispersion, and molecular diffusion. We demonstrate the applicability of the ML feature extraction method to produce a meaningful deconstruction of model outputs to discriminate between different physical processes impacting the reactants, their mixing, and the spatial distribution of the product C. The introduced ML analysis allowed us to identify additive temporal and spatial features that characterize mixing behavior. The application of the proposed NTF k approach is not limited to reactive-mixing. NTFk can be readily applied to any observed or simulated datasets that can be represented as tensors (multi-dimensional arrays) and have separable latent signatures or features.
97 MATHEMATICS AND COMPUTING↗
Materials informatics: From the atomic-level to the continuum
We report that in recent years materials informatics, which is the application of data science to problems in materials science and engineering, has emerged as a powerful tool for materials discovery and design. This relatively new field is already having a significant impact on the interpretation of data for a variety of materials systems, including those used in thermoelectrics, ferroelectrics, battery anodes and cathodes, hydrogen storage materials, polymer dielectrics, etc. Its practitioners employ the methods of multivariate statistics and machine learning in conjunction with standard computational tools (e.g., density-functional theory) to, for example, visualize and dimensionally reduce large data sets, identify patterns in hyperspectral data, parse microstructural images of polycrystals, characterize vortex structures in ferroelectrics, design batteries and, in general, establish correlations to extract important physics and infer structure-property-processing relationships. In this Overview, we critically examine the role of informatics in several important materials subfields, highlighting significant contributions to date and identifying known shortcomings. We specifically focus attention on the difference between the correlative approach of classical data science and the causative approach of physical sciences. From this perspective, we also outline some potential opportunities and challenges for informatics in the materials realm in this era of big data.
36 MATERIALS SCIENCE↗
A fast multi-fidelity method with uncertainty quantification for complex data correlations: Application to vortex-induced vibrations of marine risers
Here we develop a fast multi-fidelity modeling method for very complex correlations between high- and low-fidelity data by working in modal space to extract the proper correlation function. We apply this method to infer the amplitude of motion of a flexible marine riser in cross-flow, subject to vortex-induced vibrations (VIV). VIV are driven by an absolute instability in the flow, which imposes a frequency (Strouhal) law that requires a matching with the impedance of the structure; this matching is easily achieved because of the rapid parametric variation of the added mass force. As a result, the wavenumber of the riser spatial response is within narrow bands of uncertainty. Hence, an error in wavenumber prediction can cause significant phase-related errors in the shape of the amplitude of response along the riser, rendering correlation between low- and high-fidelity data very complex. Working in modal space as outlined herein, dense data from low-fidelity data, provided by the semi-empirical computer code VIVA, can correlate in modal space with few high-fidelity data, obtained from experiments or fully-resolved CFD simulations, to correct both phase and amplitude and provide predictions that agree very well overall with the correct shape of the amplitude response. We also quantify the uncertainty in the prediction using Bayesian modeling and exploit this uncertainty to formulate an active learning strategy for the best possible location of the sensors providing the high fidelity measurements.
42 ENGINEERING↗
In Situ Chemical Monitoring and Imaging of Contents within Microfluidic Devices Having a Porous Membrane Wall Using Liquid Microjunction Surface Sampling Probe Mass Spectrometry
The ability to observe dynamic chemical processes (e.g., signaling, transport, etc.) in vivo or in situ using nondestructive chemical imaging opens a new door to understanding the complex dynamics of developing biological systems. With the advent of “biology-on-a-chip” devices has come the ability to monitor dynamic chemical processes in a controlled environment, using these engineered habitats to capture key features of natural systems while allowing visual observation of system development. Having the capability to spatially and temporally map the chemical signals within these devices may yield new insights into the forces that drive biosystem development. Here, a porous membrane sealed microfluidic device was designed to allow normal microfluidic operation while enabling continuous, location specific sampling and chemical characterization by liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS). LMJ-SSP was used to extract fluids with nL-to-μL/min flow rates directly from selected areas of the microfluidic device without negatively impacting the device function. These extracts were subsequently characterized using MS. This technique was used to acquire MS images of the entirety of several multi-input microfluidic devices having different degrees of fluid mixing. LMJ-SSP MS imaging visualized the spatial distribution of chemical components within the microfluidic channels and could visualize chemical reactions occurring in the device. These microfluidic devices with a porous membrane wall are wholly compatible with the construction of biology-on-a-chip devices. This ultimately would enable correlation of biosystem physical structure with an evolving chemical environment
47 OTHER INSTRUMENTATION↗
Energy transfer between a passing vortex ring and a flexible plate in an ideal quiescent fluid
Recent advancements in highly deformable smart materials have lead to increasing interest in small-scale energy harvesting research for powering low consumption electronic devices. One such recent experimental study by Goushcha et al. explored energy harvesting from a passing vortex ring by a cantilevered smart material plate oriented parallel to and offset from the path of the ring in an otherwise quiescent fluid. The present study focuses on modeling this experimental study using potential flow to facilitate optimization of the energy extraction from the passing ring to raise the energy harvesting potential of the device. The problem is modeled in two-dimensions with the vortex ring represented as a pair of counter-rotating free vortices. Vortex pair parameters are determined to match the convection speed of the ring in the experiments, as well as the imposed pressure loading on the plate. The plate is approximated as a Kirchhoff-Love plate and represented as a finite length vortex sheet in the fluid domain. The analytical model matches experimental measurements, including the tip displacement, the integrated force along the entire plate length as a function of vortex ring position, and the pressure along the plate. The potential flow solution is employed in a parametric study of the governing dimensionless parameters in an effort to guide the selection of plate properties for optimal energy harvesting performance. Results of the study indicate an optimal set of plate properties for a given vortex ring configuration, in which the time-scale of vortex advection matches that of the plate vibration.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Visualizing superconductivity in a doped Weyl semimetal with broken inversion symmetry
The Weyl semimetal Mo Te 2 offers a rare opportunity to study the interplay between Weyl physics and superconductivity. Recent studies have found that Se substitution can boost the superconductivity up to 1.5 K, but suppresses the T d structure phase that is essential for the emergence of the Weyl state. A microscopic understanding of the possible coexistence of enhanced superconductivity and the T d phase has not been established so far. Here, we use scanning tunneling microscopy to study an optimally doped superconductor Mo Te 1.85 Se 0.15 with bulk T c ~ 1.5 K . By means of quasiparticle interference imaging, we identify the existence of a low-temperature T d phase with broken inversion symmetry where superconductivity globally coexists. Furthermore, we find that the superconducting coherence length, extracted from both the upper critical field and the decay of density of states near a vortex, is much larger than the characteristic length scale of the existing chemical disorder. Overall, our findings of robust superconductivity arising from a Weyl semimetal normal phase in Mo Te 1.85 Se 0.15 make it a promising candidate for realizing topological superconductivity.
36 MATERIALS SCIENCE↗
STM/S Grid LDOS Data and Analysis Code for Deciphering Majorana Zero Modes in Topological Superconductor
This dataset provides raw millikelvin scanning tunneling microscopy/spectroscopy (STM/S) grid spectroscopy data and Python analysis scripts supporting the manuscript “Deciphering Majorana Zero Modes in Topological Superconductor FeTe0.55Se0.45 with Machine-Learning-Assisted Spectral Deconvolution.” The dataset includes a raw grid spectroscopy file acquired on FeTe0.55Se0.45 at 40 mK under magnetic field, together with Python/Jupytext analysis scripts used for STM/S data processing, visualization, spectral deconvolution, Lorentzian peak fitting, feature extraction, machine-learning-assisted clustering, and figure generation. These files support the analysis of vortex-core local density of states and the identification of zero-bias-peak-related spectral components from complex in-gap states. The dataset is intended to provide a citable archival record of the data and analysis code associated with the published manuscript and to support transparency and reproducibility of the reported STM/S and machine-learning workflow.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Problems of Developing Solid Mineral Deposits on the Sea and Ocean Floor
Brief characteristics of the mineral raw material potential of the deep-sea deposits of ferromanganese nodules in the area of the Clarion-Clipperton Zone leased by Russia in the Pacific Ocean are presented. The creation at the Moscow Mining Institute (MGI) of the USSR’s first Scientific and Technical Problems Laboratory and the results of its work on extraction of minerals from the sea and ocean floor are reviewed. The research works carried out by MGI on underwater mining of ilmenite-rutile-zirconium sands on the Baltic Sea shelf and Iturup Island and tin under conditions of northern seas and the development of the technogenic placer of the East Siberian Sea are analyzed. The concept of using the kinetic energy of coaxially swirled fluid jets in hydrotransport-hoisting devices of vortex slurry preparation, which was tested in the Black Sea and an air-lift mud intake by mechanical and hydraulic loosening for extracting diamond-containing gravel-pebble rocks on the Namibia shelf is given.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Classical dynamics of vortex solitons from perturbative scattering amplitudes
Abstract We introduce a novel point-particle effective description of ANO vortex solitons in the critical Abelian Higgs Model (AHM) ind= 2 + 1 based on the small winding expansion. Identifying the effective vortices with the elementary quanta of a complex scalar field, relativistic vortex-vortex scattering amplitudes are calculated as a diagrammatic, perturbative expansion in the winding numberN. Making use of powerful techniques recently developed for analyzing the post-Minkowskian two-body problem in general relativity, we efficiently extract the contribution to the loop integrals from the classical potential region, with the resulting velocity expansion subsequently resummed to all orders. The main result of this paper is an analytic expression for the classical, vortex-vortex potential at$$ \mathcal{O} $$ O (N 2 ), or one-loop, with exact velocity dependence. By truncating the resulting effective Hamiltonian at$$ \mathcal{O} $$ O (p 2 ) we derive an analytic, perturbative expression for the metric on the 2-vortex moduli space. Finally, the emergence of the critical AHM from the classical limit of the$$ \mathcal{N} $$ N = 2 supersymmetric AHM, and the resulting constraints on the point-particle EFT is described in detail using an on-shell superspace construction for BPS states ind= 2 + 1.
Physics↗
Evaluation of Protein Extraction Methods for Metaproteomic Analyses of Root-Associated Microbes
Metaproteomics is a powerful tool for the characterization of metabolism, physiology, and functional interactions in microbial communities, including plant-associated microbiota. However, the metaproteomic methods that have been used to study plant-associated microbiota are very laborious and require large amounts of plant tissue, hindering wider application of these methods. We optimized and evaluated different protein extraction methods for metaproteomics of plant-associated microbiota in two different plant species (Arabidopsis and maize). Our main goal was to identify a method that would work with low amounts of input material (40 to 70 mg) and that would maximize the number of identified microbial proteins. We tested eight protocols, each comprising a different combination of physical lysis method, extraction buffer, and cell-enrichment method on roots from plants grown with synthetic microbial communities. We assessed the performance of the extraction protocols by liquid chromatography-tandem mass spectrometry–based metaproteomics and found that the optimal extraction method differed between the two species. For Arabidopsis roots, protein extraction by beating whole roots with small beads provided the greatest number of identified microbial proteins and improved the identification of proteins from gram-positive bacteria. For maize, vortexing root pieces in the presence of large glass beads yielded the greatest number of microbial proteins identified. Based on these data, we recommend the use of these two methods for metaproteomics with Arabidopsis and maize. Furthermore, detailed descriptions of the eight tested protocols will enable future optimization of protein extraction for metaproteomics in other dicot and monocot plants.
59 BASIC BIOLOGICAL SCIENCES↗
Numerical investigation of the influence of shear and thermal stratification on the wind turbine tip‐vortex stability
Summary The interaction between wind turbine wakes and atmospheric turbulence is characterised by complex dynamics. In this study, two major components of the atmospheric boundary layer dynamics have been isolated, namely, the mean velocity profile shear and the thermal stratification, to examine their impact on the near‐wake development by undertaking a series of highly resolved large‐eddy simulations. Subsequently, instantaneous flow fields are extracted from the simulations and used to conduct Fourier analysis and proper orthogonal decomposition (POD) and compute the mean kinetic energy fluxes by different POD modes to better understand the tip‐vortex instability mechanisms. Our findings indicate that shear can significantly affect the breakup of the wind turbine tip‐vortices and the shape and stable length of the wake, whereas thermal stratification seems to only have limited contribution to the spatial development of the near‐wake field. Finally, our analysis shows that the applied perturbation frequency determines the tip‐vortex breakup location as it controls the onset of the mutual inductance instability.
17 WIND ENERGY↗
Feasibility of an experiment on clumping induced by the Crow instability along a shocked cylinder
The growth of three-dimensional perturbations subject to the Crow instability along a vortex dipole resulting from the passage of a shock wave through a heavy gaseous cylinder is examined numerically. A linear stability analysis is performed based on geometric parameters extracted from two-dimensional simulations to determine the range of unstable wavenumbers, which is found to extend from 0.0 to 1.3 when normalized by the core separation distance. The analysis is then verified by comparison to three-dimensional simulations, which clearly show the development of the instability and the pinch-off of the vortex dipole into isolated vortex rings, which manifest as clumps of the original cylinder material. A scaling law is developed to determine the relevant spatiotemporal scales of the instability development, which is then used to assess the feasibility of a high-energy-density experiment visualizing clump formation. Specifically, a shocked cylinder with an initial diameter of 100 μm consisting of a perturbation of approximate wavelength and amplitude of 600 and 10 μm, respectively, is expected to form clumps resulting from the Crow instability approximately 40 ns after it is shocked, with dynamics which can be readily visualized on the Omega EP laser facility.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Vortex entropy and superconducting fluctuations in ultrathin underdoped Bi 2 Sr 2 CaCu 2 O 8+x superconductor
Vortices in superconductors can help identify emergent phenomena but certain fundamental aspects of vortices, such as their entropy, remain poorly understood. Here, we study the vortex entropy in underdoped Bi 2 Sr 2 CaCu 2 O 8+x by measuring both magneto-resistivity and Nernst effect on ultrathin flakes (≤2 unit-cell). We extract the London penetration depth from the magneto-transport measurements on samples with different doping levels. It reveals that the superfluid phase stiffness p s scales linearly with the superconducting transition temperature T c , down to the extremely underdoped case. On the same batch of ultrathin flakes, we measure the Nernst effect via on-chip thermometry. Together, we obtain the vortex entropy and find that it decays exponentially with T c or p s . We further analyze the Nernst signal above T c in the framework of Gaussian superconducting fluctuations. The combination of electrical and thermoelectric measurements in the two-dimensional limit provides fresh insight into high temperature superconductivity.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
In Situ Magnetic Flux Vortex Visulatization in Time-Dependent Ginzburg-Landau Superconductor Simulations
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feature extraction and tracking↗
Implications of Shear and Thermal Stratification on Wind Turbine Tip-Vortex Stability
The interaction between wind turbines in a wind farm through their wakes is a phenomenon that has been studied for decades and is still relevant today. Turbines clustered together in arrays will often operate in the wake of other upstream turbines which may lead to significant power losses and fatigue loads. For modern large-scale wind turbines, the mean shear velocity profile and thermal stratification are major components of the atmospheric boundary layer so it is important to understand their impact on near-wake development. Additionally, veer is present due to the rotation of the Earth. The impact of shear, thermal stratification and veer on the stable wake length of turbines with a dynamic control strategy is studied numerically in this work using a suite of highly resolved large-eddy simulations. Instantaneous flow fields are extracted from the simulations and used to conduct proper orthogonal decomposition (POD) and compute the mean kinetic energy fluxes by different POD modes to better understand the tip-vortex instability mechanisms. Our findings show that the dynamic pitch control scheme is able to shorten the stable wake length to about 1.5R in uniform flow. Shear can significantly affect the break up of wind turbine tip-vortices as well as the shape and stable length of the wake, whereas thermal stratification seems to only have limited contribution to the spatial development of the near-wake field. Veer causes the wake boundary to skew but has a limited impact on the wake length.
length thermal stratification↗
Off-equilibrium infrared structure of self-interacting scalar fields: Universal scaling, vortex-antivortex superfluid dynamics, and Bose-Einstein condensation
Here, we map the infrared dynamics of a relativistic single-component (N=1) interacting scalar field theory to that of nonrelativistic complex scalar fields. The Gross-Pitaevskii (GP) equation, describing the real-time dynamics of single-component ultracold Bose gases, is obtained at first nontrivial order in an expansion proportional to the powers of λΦ 2 /m 2 where λ, Φ, and m are the coupling constant, the scalar field, and the particle mass respectively. Our analytical studies are corroborated by numerical simulations of the spatial and momentum structure of overoccupied scalar fields in (2+1)-dimensions. Universal scaling of infrared modes, vortex-antivortex superfluid dynamics, and the off-equilibrium formation of a Bose-Einstein condensate are observed. Our results for the universal scaling exponents are in agreement with those extracted in the numerical simulations of the GP equation. As in these simulations, we observe coarsening phase kinetics in the Bose superfluid with strongly anomalous scaling exponents relative to that of vertex resummed kinetic theory. Our relativistic field theory framework further allows one to study more closely the coupling between superfluid and normal fluid modes, specifically the turbulent momentum and spatial structure of the coupling between a quasiparticle cascade to the infrared and an energy cascade to the ultraviolet. We outline possible applications of the formalism to the dynamics of vortex-antivortex formation and to the off-equilibrium dynamics of the strongly interacting matter formed in heavy-ion collisions.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Turbulent flow characteristics in an 84-pin rod bundle for typical and damaged spacer grids
Hexagonal rod bundles arranged in a tightly packed triangular lattice are extensively used for heat transfer and energy generation applications. Staggered spacer grids are used to maintain the structural integrity of gas-cooled fast reactor (GFR) fuel assemblies, while inducing localized turbulence in flow. Damage to these spacer grids results in a disruption of flow fields within these hexagonal fuel bundles. Experimental flow visualizations are critical to identify the differences in local flow properties that the structural damage may cause. This experimental research investigates the flow-field characteristics at a near-wall and center plane in a prototypical 84-pin GFR fuel assembly. Newly installed typical spacers and spacers subject to naturally occurring damage due to material degradation over prolonged experimentation were investigated. Velocity fields were acquired by utilizing the matched-index-of-refraction method to obtain time-resolved particle image velocimetry measurements for a Reynolds number of 12 000. Reynolds decomposition statistical results divulged differences in the time-averaged velocity, velocity fluctuations, flow anisotropy, and Reynolds stress distributions. Galilean decomposition demarcated the influence of spacer grid damage on the velocity fields. To extract turbulent structures and elucidate mechanisms of flow instabilities, proper orthogonal decomposition analysis was employed. Reduced order flow reconstructions enabled the application of vortex identification algorithms to determine the spatial and statistical characteristics of vortices generated. This research work provides unique experimental data on the spacer grid condition-dependent flow. The results offer a deeper understanding of fluid dynamics behavior to support GFR rod bundle design efforts and computational fluid dynamics model validation.
36 MATERIALS SCIENCE↗