Field Generation Research Articles

The uniform and robust 8-inch CVD diamond plate generated by dual-magnetic field controlled DC Jet CVD

Diamond is a highly attractive material for many applications in material science, engineering, chemistry, and biology because of its favorable properties. The preparation of large-area freestanding diamond plate can greatly reduce the production cost of diamond and promote the industrialization of diamond. In this study, the dual-magnetic field mode was introduced to optimize the magnetic field distribution in direct current arc plasma jet chemical vapor deposition (DC Jet CVD) system, and the arc plasma was effectively controlled under the coupling of electric field and magnetic field. The uniformity of the plasma distribution above the substrate surface is significantly improved, resulting in long-term stable and uniform growth of the 8-inch freestanding diamond plate. The influence of dual-magnetic field mode on magnetic field generation, arc feature, and reactive group distribution was studied. 8-inch freestanding diamond plates with an average thickness of 2.8 mm were prepared by dual-magnetic controlled DC Jet CVD. The results showed that the 8-inch diamond plate preferred a high (220) orientation, and the deviation of thickness of which was around 10 % of the averaged values. Raman spectroscopy of diamond revealed a 6.6 cm−1 of full width at half maximum (FWHM) and calculated 1.20 GPa compressive stress in the 8-inch diamond plate. By means of mechanical and thermal property measurements, the large area diamond plate shows a robust structure with the average values of three-point bending fracture strength of 987.2 MPa, and extremely high thermal conductivity of 1797.8 W/(m·k) as well. The deviation of three-point bending fracture strength and the thermal conductivity over the 8-inch diamond plate was around 7.9 % and 12.6 % of the respective averaged values.

Combinatorial Approach to Find Nanoparticle Assemblies with Maximum Surface-Enhanced Raman Scattering.

Plasmonic nanoparticles exhibit unique properties that distinguish them from other nanomaterials, including vibrant visible colors, the generation of local electric fields, the production of hot charge carriers, and localized heat emission. These properties are particularly enhanced in the narrow nanogaps formed between nanostructures. Therefore, creating nanogaps in a controlled fashion is the key to achieving a fundamental understanding of plasmonic phenomena originating from the nanogaps and developing advanced nanomaterials with enhanced performance for diverse applications. One of the most effective approaches to creating nanogaps is to assemble individual nanoparticles into a clustered structure. In this study, we present a fast, facile, and highly efficient method for preparing core@satellite (CS) nanoassembly structures using gold nanoparticles of various shapes and sizes, including nanospheres, nanocubes (AuNCs), nanorods, and nanotriangular prisms. The sequential assembly of these building blocks on glass substrates allows us to obtain CS nanostructures with a 100% yield within 4 h. Using 9 different building blocks, we successfully produce 16 distinct CS nanoassemblies and systematically investigate the combinations to search for the highest Raman enhancement. We find that the surface-enhanced Raman scattering (SERS) intensity of AuNC@AuNC CS nanoassemblies is 2 orders of magnitude larger than that of other CS nanoassemblies. Theoretical analyses reveal that the intensity and distribution of the electric field induced in the nanogaps by plasmon excitation, as well as the number of molecules in the interfacial region, collectively contribute to the unprecedentedly large SERS enhancement observed for AuNC@AuNC. This study not only presents a novel assembly method that can be extended to produce many other nanoassemblies but also identifies a highly promising SERS material for sensing and diagnostics through a systematic search process.

GAN-based generation of realistic compressible-flow samples from incomplete data

Predictive sampling of compressible flows is an important aspect of aerodynamic design, analysis, and optimization. The process is usually done by generating flow fields from computational fluid dynamics (CFD) simulations and solving governing evolution equations, from which quantities of interest (QoI) are obtained by post-processing. With this study, we propose a data-driven approach for the predictive sampling of compressible flows around airfoils. This paper demonstrates the potential of generative adverserial networks (GANs), particularly the Pix2Pix model, to predict supersonic flow fields around airfoils. Building upon the similarities between our generator architecture and FlowGAN, which also employs the Pix2Pix model, our work extends the capabilities of FlowGAN to encompass supersonic flows and higher-resolution predictions. Our methodology introduces a multi-variable prediction framework, enabling the simultaneous prediction of various flow variables, including pressure, velocity, and density. We achieve the generation of flow fields with a relative error of less than 1.5%. We utilize the same framework to train a model capable of generating synthetic schlieren images, exhibiting a similarity structure index greater than 0.97, underscoring the high-fidelity generation capacity of our model. Addressing the challenges of generalization to unseen Mach numbers and angles of attack, we adopt transfer learning. By fine-tuning a pre-trained model on a limited number of examples from the unseen parameters, we obtain an improved prediction of shock wave positions. Furthermore, we present a practical application of our methodology by reconstructing flow fields from schlieren images. This application could prove valuable in real-world scenarios, providing a useful tool for studying and comprehending complex flow phenomena.

Nonlinear parametric generation in a four-level inverted-type quantum well nanostructure

In this study, we introduce an innovative semiconductor quantum well (SQW) nanostructure, which exhibits a unique four-level configuration arranged in an inverted Y-shape. This configuration enables interaction with three laser fields and demonstrates the intriguing nonlinear phenomenon of parametric generation. Our investigation delves into a wide range of parametric conditions, aiming to understand the profound impact of various system parameters on the generation and propagation of new light fields within this groundbreaking nanostructure. By employing a combination of analytical and numerical methods, we not only reveal the potential for precise manipulation of coherence among energy levels but also showcase its practical implications — high-efficiency and tunability in the parametric generation process. This pioneering scheme represents a significant advancement in the field of SQW structures, bridging the gap between theoretical exploration and practical application. Our findings promise exciting prospects for the development of novel light sources and optical devices based on SQW structures, thereby pushing the boundaries of what is achievable in various applications and setting new standards for the state-of-the-art in this domain.

Stochastic analysis and reliability assessment of critical RC structural components considering material properties uncertainty

The unavoidable heterogeneity in the mechanical characteristics of concrete is widely acknowledged. Although it is widely considered as either perfectly correlated or entirely independent random variables in engineering practice; however, such treatment is illogical, and the outcomes may be deceptive. In high-rise buildings comprised of multiple structural components, it is crucial to consider the material properties’ spatial variability (MPSV) to obtain a reliable structural response and avoid damage to these structures. To this end, three main components, including column, rectangular shear wall, and U-shaped shear wall, are considered herein to investigate their stochastic response. The MPSV is represented by a covariance matrix decomposition-based random field generator combined with a GF-discrepancy-based point selection strategy to generate samples efficiently. A simplified strategy is developed to represent the random field for the U-shaped wall. Moreover, the probability density evolution method combined with the extreme value event is employed to obtain the failure probability of the studied components, where failure probabilities of 18%, 23%, and 32% are recorded for the studied RC column, rectangular shear wall, and U-shaped shear wall, respectively. Furthermore, different failure modes were identified and could not be determined through the deterministic analysis, highlighting the importance of accounting for material uncertainty. The proposed framework proved that the stochastic response and non-linear behavior of the considered components could be well captured and provide full perspective about the uncertainty quantification and reliability assessment and can be further implemented to capture the stochastic response and safety assessment of high-rise buildings.

Physical conversion and superposition of optical skyrmion topologies

Optical skyrmions are quasiparticles with nontrivial topological textures that have significant potential in optical information processing, transmission, and storage. Here, we theoretically and experimentally achieve the conversion of optical skyrmions among Néel, Bloch, intermediate skyrmions, and bimerons by polarization devices, where the fusion and annihilation of optical skyrmions are demonstrated accordingly. By analyzing the polarization pattern in Poincaré beams, we reveal the skyrmion topology dependence on the device, which provides a pathway for the study of skyrmion interactions. A vectorial optical field generator is implemented to realize the conversion and superposition experimentally, and the results are in good agreement with the theoretical predictions. These results enhance our comprehension of optical topological quasiparticles, which could have a significant impact on the transfer, storage, and communication of optical information.

Germination of bean seeds (Vigna unguiculata L. Walp.) in strong electric fields

This paper presents a tutorial for the germination of bean seeds (Vigna unguiculata L. Walp.) in strong electrostatic fields up to 1240 V/cm. The seeds were allowed to germinate under different electric field strengths for 48 h. Although most of such germination experiments did not show any visible effect, the field strength of 945 V/cm strongly increased the seedling's vigor during the early growth stage. In the end, 30 % more yield was obtained from stimulated seeds when compared to the control group. This article postulates for the first time a hypothesis of the mechanism of action of the electric field during germination. In biological cells of any species, water confined between narrow surfaces can undergo a phase transition that shifts its melting point to higher temperatures when an external electric field is applied. This effect has already been known as electrofreezing, and has been confirmed by several experimental and molecular modeling studies. As a consequence, the transport kinetics of molecules across cell organelle membranes might be altered, which in turn leads to different plant properties.With emphasis on the presented method, this work reports:•An inexpensive electric circuit for the generation of strong electric fields•Instructions regarding the setup and operation of an adequate germination chamber

Optical Super‐Resonances in Mesoscale Dielectric Cenosphere: Giant Magnetic Field Generations

AbstractResonant light scattering by mesoscale dielectric spheres has received enormous attention and found many interesting applications. The recently emerged field of Mesotronics provides novel opportunities for wavelength‐scaled optics and new fundamental aspects are still being uncovered. It has recently been demonstrated that high‐order Mie resonances can be excited in homogeneous low‐dissipation mesoscale dielectric spheres, leading to the generation of intense magnetic fields. This article describes a simple and effective way to drastically enhance the superresonance effect. Proof‐of‐principle results for the first time show that yet one more novel phenomenon of increasing the intensity of the magnetic field without changing the resonant Mie size parameter of the sphere by introducing an air cavity. In such a dielectric cenosphere (from two Greek words “kenos”‐hollow and “sphaira”‐sphere), by correct choice of the air cavity size, it is possible to increase the intensity of the electromagnetic fields at the poles of the sphere by an order of magnitude due to increasing of the amplitude of resonant partial wave coefficient.

Reconfigurable generation of chiral optical fields with multiple selective degrees of freedom.

Chiral optical fields caused by vortex beams possessing orbital angular momentum (OAM) can be used to fabricate helically structured materials and identify chiral molecules, in which the materials or molecules are associated with the character of the irradiated light. However, previously reported chiral optical fields can control only some of the parameters including the number of fringes, size, ellipticity, orientation, and local intensity distribution, which may hamper their applications. Thus, in this work, we propose both theoretically and experimentally an approach to fabricate chiral optical fields with five separately controllable degrees of freedom by overlapping two anisotropic vortices whose wavefronts have a nonlinear phase variation with the azimuthal angle. The local intensity distribution, number of fringes, size, orientation, and ellipticity of the chiral optical field can be dynamically controlled by adjusting the nonlinear coefficient, topological charges, axicon parameter, rotation angle, and stretching factor of the anisotropic vortices. Furthermore, the OAM density was investigated and proven to be continuously enhanced with the variation of the field's local intensity distribution, which gives the proposed approach the ability to continuously manipulate the OAM density of chiral optical fields. This work, supporting chiral optical fields by five separately controllable parameters, may make the applications of chiral optical fields in the fields of nanostructure fabrication and optical tweezers more flexible.

Direct Sampling for Spatially Variable Extreme Event Generation in Resampling‐Based Stochastic Weather Generators

AbstractResampling‐based weather generators simulate new time series of weather variables by reordering the observed values such that the statistics of the simulated data are consistent with the observed ones. These generators are fully data‐driven, easy to implement, and capable of reproducing the dynamics among weather variables. However, although the simulated time series is new, the weather fields produced at arbitrary time steps are replicas of those found in observations, limiting the spatial variability of simulations and preventing the generation of extreme weather fields beyond the range of observed values. To address these limitations, we propose the integration of the Direct Sampling algorithm—a data‐driven method for producing simulations—into resampling‐based weather generators. By incorporating Direct Sampling as a post‐processing step on the outputs of the weather generator, we enhance the spatial variability of the generated weather fields and enable the generation of extreme weather fields. We introduce an approach for generating out‐of‐sample extreme weather fields using Direct Sampling. This method involves utilizing a set of control points in conjunction with Direct Sampling, where the values of these control points are informed by return period analysis. The proposed approach is validated using precipitation, temperature, and cloud cover weather fields in a region of northwest India. The experimental results confirm that Direct Sampling enhances the spatial variability of the weather fields and facilitates the generation of out‐of‐sample precipitation fields that accurately adhere to the spatial statistics provided by return precipitation level maps, as well as the observed precipitation weather field employed in the analysis.

Period bouncers as detached magnetic cataclysmic variables

Context. The general prediction that more than half of all cataclysmic variables (CVs) have evolved past the period minimum is in strong disagreement with observational surveys, which show that the relative number of these objects is just a few percent. Aims. Here, we investigate whether a large number of post-period minimum CVs could detach because of the appearance of a strong white dwarf magnetic field potentially generated by a rotation- and crystallization-driven dynamo. Methods. We used the MESA code to calculate evolutionary tracks of CVs incorporating the spin evolution and cooling as well as compressional heating of the white dwarf. If the conditions for the dynamo were met, we assumed that the emerging magnetic field of the white dwarf connects to that of the companion star and incorporated the corresponding synchronization torque, which transfers spin angular momentum to the orbit. Results. We find that for CVs with donor masses exceeding ∼0.04 M⊙, magnetic fields are generated mostly if the white dwarfs start to crystallize before the onset of mass transfer. It is possible that a few white dwarf magnetic fields are generated in the period gap. For the remaining CVs, the conditions for the dynamo to work are met beyond the period minimum, when the accretion rate decreased significantly. Synchronization torques cause these systems to detach for several gigayears even if the magnetic field strength of the white dwarf is just one MG. Conclusions. If the rotation- and crystallization-driven dynamo – which is currently the only mechanism that can explain several observational facts related to magnetism in CVs and their progenitors – or a similar temperature-dependent mechanism is responsible for the generation of magnetic field in white dwarfs, most CVs that have evolved beyond the period minimum must detach for several gigayears at some point. This reduces the predicted number of semi-detached period bouncers by up to ∼60 − 80%.

Convolutional-neural-network-based DES-level aerodynamic flow field generation from URANS data

The present paper culminates several investigations into the use of convolutional neural networks (CNNs) as a post-processing step to improve the accuracy of unsteady Reynolds-averaged Navier–Stokes (URANS) simulations for subsonic flows over airfoils at low angles of attack. Time-averaged detached eddy simulation (DES)-generated flow fields serve as the target data for creating and training CNN models. CNN post-processing generates flow-field data comparable to DES resolution, but after using only URANS-level resources and properly training CNN models. This document outlines the underlying theory and progress toward the goal of improving URANS simulations by looking at flow predictions for a class of simple, two-dimensional, streamlined profiles (i.e., an NACA0006 airfoil simulated at Mach 0.3 over an angle-of-attack range of −8° to 8°). After several design iterations, two trained CNN models predict the pressure and density fields immediately surrounding the airfoils, and those results compare well to DES ground truth data. Generally, the trained models match the DES resolution for the model training data. However, to accurately predict the flow conditions outside of the training set, other approaches are necessary. For this portion of the research, all computational fluid dynamic calculations use NASA’s fully-unstructured-Navier–Stokes-3D solver. The rest of the software comes from Python libraries within the public domain to encourage follow-on research. These libraries include TensorFlow for machine learning models and the sequential model-based optimization to generate the algorithm configuration for hyperparameter optimization.

Generation of jet-forming plasma bunch with gigagauss axial magnetic field from impact of linearly polarized laser on microtube targets

Generation of a thin plasma jet with embedded gigagauss axial magnetic fields from the frontal impact of a short linearly polarized laser pulse on an overdense microtube target is considered. It is a new scheme of axial magnetic field generation without initial laser angular momentum. Three-dimensional particle-in-cell simulations show that the space-charge field of the laser expelled tube-front electrons will pull out carbon ions to form at the tube entrance a long-living low-density plasma bunch with gigagauss magnetic fields. The front center of the plasma bunch then stretches forward to form a thin gigagauss-magnetized plasma jet, which survives for sub-picosecond after the core of the laser has passed through the tube.

Multi-pole magnetorheological shear thickening polishing on inner surface of aluminum alloy slender tubes

The aluminum alloys slender tubes with high surface quality are required to improve the components performance. The inner surface polishing of slender tubes becomes a challenge because of the machining space limitation. In this work, a multi-pole magnetorheological shear thickening polishing (MP-MSTP) method, combining the dual excitation of magnetorheological principles and shear thickening behavior, is proposed for aluminum alloy slender tubes polishing. The magnetic field generator was designed integrating four cylindrical Nd-Fe-B radial magnetic poles. The magnetic flux density is investigated in the polishing zone based on finite element analysis (FEA) and experimental measurements. Mathematical modeling of material removal rate (MRR) was established based on single abrasive particle. The feasibility of the MP-MSTP method for aluminum alloy slender tube was verified by computational fluid dynamics (CFD) simulation analysis and experimental measurements. Polishing experiments were carried out on the inner surface of aluminum alloy slender tubes to investigate the effect of various processing parameters on surface roughness, including carbonyl iron particles (CIPs) and silicon carbide (SiC) abrasive particle sizes, working gap and workpiece rotational speed. The surface roughness was reduced to 155 nm from the initial 480 nm under the optimal polishing parameters. A smooth surface without micro-convex peaks and deep scratches was obtained after 50 min polishing based on ultra-depth-of-field microscope and SEM observation.

Synthesis of lanthanum manganite powders via combustion reactions: some aspects of the influence of magnetic field and charge generation in precursors on the formation of properties

Synthesis of lanthanum manganite powders via combustion reactions: some aspects of the influence of magnetic field and charge generation in precursors on the formation of properties

Why cross fields are not equivalent to quadrilateral meshes

Isogeometric Analysis (IGA) necessitates quadrilateral meshing owing to the utilization of NURBS or other locally tensor-product spline functions as the foundation for its analysis. It is a widely held misconception that the generation of cross fields over the surface domain – a common precursor to quad-mesh construction – establishes equivalence between cross fields and quad-meshes. In this study, we dispel this notion by presenting theorems that distinctly delineate the singularity configurations of both cross fields and quad-meshes. It is posited that these can be viewed as characteristic classes of different fiber bundles, where cross field singularity aligns with the cross fiber bundle and structured mesh singularity corresponds to holomorphic line bundles. As a result, the conditions necessitating quad-mesh singularities are decidedly more stringent than those for cross field singularities. This explains a notable query in the field: the absence of a 3-5 quad-mesh (a quad-mesh with two singularities with topological valence 3 and 5 respectively) on a torus. Additionally, the theoretical framework is broadened to incorporate other types of structured meshes. The formulated theorems give rise to practical algorithms for cross field construction and structured mesh generation. The efficacy and applicability of these algorithms are corroborated through numerical examples that not only validate the theoretical findings but also underscore their practical usability.

Small-scale Kazantsev-Kraichnan dynamo in a MHD shell approach

The small-scale magnetic energy generation in a turbulent velocity field is studied by two different approaches. One of them is based on the Kazantsev-Kraichnan model developed for turbulence with short-time velocity correlations, and the other uses the shell model of magnetohydrodynamic turbulence, describing the turbulent energy cascade on a finite number of spectral shells. We have found that the injection of weak magnetic field at the initial moment in both models leads to an exponential growth of magnetic energy and tried to determine whether these effects are of the same or different nature. The investigations have shown that the rates of growths and magnetic energy spectra in two approaches can be very much different, which can be attributed to the contradictions of the model assumptions and unknown correlation time. The discussion of these contradictions allows us to formulate a possible explanation, which is likely related to the fact that the small-scale magnetic field generation is under the influence of some spectral subrange, rather than the entire kinetic spectrum. Varying the correlation time of the velocity field and considering the spectral regions, we have determined the range of kinetic energy spectrum responsible for the small-scale dynamo generation.

Lithiophilic and Conductive CuO-Cu2O-Cu Microspheres with Controlled Void Structure via Spray Pyrolysis for Improved Lithium Metal Anode Performance

Lithium metal anodes (LMAs) have attracted significant attention owing to their high theoretical capacity and lowest redox potential. However, dendritic growth of lithium limits its practical application. Controlling lithium deposition through structuring host materials for LMAs has been widely studied. In this study, a unique structured CuO-Cu2O-Cu composite microsphere is synthesized through facile one-step spray pyrolysis process as a new lithium host material for LMAs. During lithium deposition, lithium ions preferred to be adsorbed on composite microspheres due to the electric field generated from the metallic Cu-based conductive matrix. The adsorbed ions reacted with lithiophilic copper oxides to form copper and Li2O, promoting the generation of a uniform electric field and ion transfer. Moreover, hollow structure can guide lithium to be encapsulated inside the structures, enabling effective suppression of dendritic lithium growth. As a result, this composite microsphere is capable to store lithium with high areal capacity of 5.0 mAh cm-2 without dendritic growth of lithium. Consequently, the composite microspheres exhibit a coulombic efficiency above 99% for more than 200 cycles at a current density of 1.0 mA cm-2 as an asymmetric cell and show low voltage hysteresis of 19 mV for more than 1,000 h as a symmetric cell. This study demonstrates that the designed microstructures with an appropriate ratio of conductive and lithiophilic matrices with sufficient pore structures provide promising cycle performance as host materials for lithium metal anode.

Suppression of small-scale dynamo in time-irreversible turbulence

ABSTRACT The conventional theory of small-scale magnetic field generation in a turbulent flow considers time-reversible random flows. However, real turbulent flows are known to be time irreversible: the presence of energy cascade is an intrinsic property of turbulence. We generalize the ‘standard’ model to account for the irreversibility. We show that even small time asymmetry leads to significant suppression of the dynamo effect at low magnetic Prandtl numbers, increases the generation threshold, and may even make generation impossible for any magnetic Reynolds number. We calculate the magnetic energy growth rate as a function of the parameters of the flow.

A field theory approach to the statistical kinematic dynamo

Variations in the geomagnetic field occur on a vast range of time scales, from milliseconds to millions of years. The advent of satellite measurements has allowed for detailed studies of short timescale geomagnetic field behaviour, but understanding its long timescale evolution remains challenging due to the sparsity of the paleomagnetic record. This paper introduces a field theory framework for studying magnetic field generation as a result of stochastic fluid motions. Starting from a stochastic kinematic dynamo model (the Kazantsev kinematic model), we derive statistical properties of the magnetic field that may be compared to observations from the paleomagnetic record. The fluid velocity is taken to be a Kraichnan field with general covariance, which acts as a random forcing obeying Gaussian statistics. Using the Martin-Siggia-Rose-Janssen-de Dominicis formalism, we compute the average magnetic field response function for fluid velocities with short correlation time. From this we obtain an estimate for the turbulent contribution to the magnetic diffusivity, and find that it is consistent with results from mean-field dynamo theory. This framework presents much promise for studying the geomagnetic field in a stochastic context.