Large Field Research Articles

Low-carbon Treatment and Remediation of Oil Sludge in Mid-to-high Latitude Regions: A Coupled Approach of Freeze-Thaw and Supercritical CO2 Extraction

The oil sludge produced while extracting large oil and gas fields in the middle and high latitude regions has caused serious pollution to the surrounding soil. The key to solving this problem in the future is to unify the remediation of soil and the treatment of oil sludge. This study uses supercritical carbon dioxide(scCO2) technology to construct a low-carbon method, providing a new approach to achieve this goal. The study determines the optimal extraction conditions for black calcareous soil with 15% oil content to be 55 °C, 25 MPa, and 90 min through single factor and response surface experiments. Experiments on the scCO2 extraction coupled with freeze-thaw cycles show that oil sludge with a water content of 10% can improve the extraction efficiency of scCO2 by about 2.69% after less than five freeze-thaw cycles. The study also compares the extraction efficiency of the four soils, with a difference of 6.03% observed under the same conditions. Additionally, we analyze the impact of the extraction process on changes in the properties of the oil and soil in the oil sludge. Comprehensive tests, including scanning electron microscope (SEM), nutrient detection, X-ray powder diffractometer (XRD), fourier transform infrared spectroscopy (FTIR), and Gas Chromatography (GC), have been conducted. Results show that standalone scCO2 extraction can remove up to 98.2% of petroleum hydrocarbons from the oil sludge, while simultaneously causing small changes to the soil microstructure and the crystal structure of the oil sludge. Furthermore, this process does not lead to a significant depletion of key nutrients or the generation of new pollutants.

Large-field high-resolution X-ray AKB microscope for measuring hydrodynamic instabilities at the SG-III prototype laser facility.

X-ray imaging with a large field of view (FOV) and high resolution is extremely important for Rayleigh-Taylor instability measurement with a small amplitude and high spatial frequency in laser inertial confinement fusion. We developed an advanced Kirkpatrick-Baez (AKB) microscope based on the quadratic-aberration theory to realize a large FOV and high resolution. This microscope was assembled and tested in a laboratory, and it was then successfully applied for imaging the hydrodynamic instability of a perturbation target in implosion experiments at the Shenguang-III prototype laser facility. Imaging results demonstrate that the AKB microscope can achieve an optimal resolution of ~ 0.53μm and ~ 0.40μm and a spatial resolution of < 1.5μm within a 300-µm FOV and < 4.5μm in a 1-mm FOV.

Decoding Continuous Tracking Eye Movements from Cortical Spiking Activity.

Eye movements are the primary way primates interact with the world. Understanding how the brain controls the eyes is therefore crucial for improving human health and designing visual rehabilitation devices. However, brain activity is challenging to decipher. Here, we leveraged machine learning algorithms to reconstruct tracking eye movements from high-resolution neuronal recordings. We found that continuous eye position could be decoded with high accuracy using spiking data from only a few dozen cortical neurons. We tested eight decoders and found that neural network models yielded the highest decoding accuracy. Simpler models performed well above chance with a substantial reduction in training time. We measured the impact of data quantity (e.g. number of neurons) and data format (e.g. bin width) on training time, inference time, and generalizability. Training models with more input data improved performance, as expected, but the format of the behavioral output was critical for emphasizing or omitting specific oculomotor events. Our results provide the first demonstration, to our knowledge, of continuously decoded eye movements across a large field of view. Our comprehensive investigation of predictive power and computational efficiency for common decoder architectures provides a much-needed foundation for future work on real-time gaze-tracking devices.

Half-wavelength-pitch silicon optical phased array with a 180° field of view, high sidelobe suppression ratio, and complex-pattern beamforming

Solid-state optical beam steering devices desire a large field of view (FOV), good beam quality, and reconfigurable beamforming of complex patterns, which are not available in a single system yet. Having not been demonstrated, an active beamformer using an optical phased array (OPA) could potentially fulfill these requirements simultaneously, because it can control both the wavefront and beam pattern. Half-wavelength-pitch OPAs theoretically can achieve the three requirements concurrently, but suffer from crosstalk. Most previous efforts focus on mitigating/avoiding crosstalk. Instead, here we appreciate its existence and propose/demonstrate a programmable architecture to compensate for it. Using a tree of composite variable splitters with a full splitting-ratio range, we achieve arbitrary amplitude/phase modulation to pre-correct scrambled phase/amplitude by crosstalk. With comprehensive stray-light minimization strategies, the sidelobe suppression ratio (SLSR) is significantly improved. Our design achieves a 180∘ FOV, a peak SLSR of 24 dB, and complex-pattern beamforming simultaneously in a half-wavelength-pitch 64-waveguide array. Within the ±60∘ range, a SLSR of &gt;20dB is achieved. Our OPA demonstrates Bayliss difference, pulse-shaped, and asymmetric three-beam patterns with high SLSRs of &gt;20dB, ∼10dB, and &gt;18dB, respectively. These performance metrics are important for various applications in light detection and ranging, imaging, and communication.

A pilot study to directly estimate radiation-induced mutation in large Japanese field mouse duo sample, mother and offspring, excluding unknown father, using ddRAD sequencing.

DNA mutations are one of the effects of radiation exposure. A large amount of radioactive materials was released into the environment from the Fukushima Daiichi Nuclear Power Plant after a major earthquake and tsunami. Wild animals and plants living in highly radiation-contaminated areas are constantly exposed to high doses of radiation, and concerns occur about its effects on their health and the next generations. As a pilot study, double-digest restriction site-associated DNA (ddRAD) sequencing was conducted to assess the incidence of mutations in wild large Japanese field mice collected from the evacuation area. The optimal combination of restriction enzymes, encompassing the functionally important coding regions, was selected using in silico analysis. These enzymes were used for ddRAD sequence analysis of females and their fetuses to evaluate mutation rates. The results indicated that no significant differences were observed in mutation rates between mothers and fetuses in the study areas.

A novel deep learning‐based technique for efficient characterization of engineered cementitious composites cracks for durability assessment

AbstractEngineered Cementitious Composites also known as Strain‐hardening cementitious composites (SHCCs) has unique cracking patterns like cracks that have tiny widths and showcase high density. All of this makes it difficult and laborious to compute crack parameters from crack patterns. Unfortunately, this is an essential part of assessing durability and micromechanical modeling. SHSnet is developed to perform end‐to‐end semantic segmentation of SHCC cracks. SHSnet is efficient, attention based deep encoder‐decoder network with large receptive field. Loss function based on Tversky function were used for training the model. SHSnet with loss function shows promising result with mPrecision, mF1Score and mIoU of 0.87, 0.84 and 0.83 respectively for complex SHCC cracks while requiring at least an order of fewer computational parameters than those in the literature. An image processing unit is then used to estimate the width, number, and length of the cracks from the segmentation mask. Test results show that the computed crack parameters with SHSnet are exactly the same as that computed with an optical microscope but require ~100× less time. Results demonstrate that SHSnet works equally well in SHCCs with different surface textures, crack density, and widths; the final result was far superior to a conventional technique. This technique also shows promising results in an automatic evaluation of crack parameters relevant to durability and visualizing crack patterns even in the presence of artifacts during progressive testing. The results also demonstrate the necessity to accurately and densely calculate crack length and maximum crack width; else the durability results are expected to be significantly more conservative than the actual value.

Broad Instantaneous Bandwidth Microwave Spectrum Analyzer with a Microfabricated Atomic Vapor Cell

We report on broad instantaneous bandwidth microwave spectrum analysis with hot Rb87 atoms in a microfabricated vapor cell in a large magnetic field gradient. The sensor is a MEMS atomic vapor cell filled with isotopically pure Rb87 and N2 buffer gas to localize the motion of the atoms. The microwave signals of interest are coupled through a coplanar waveguide to the cell, inducing spin-flip transitions between optically pumped ground states of the atoms. A static magnetic field with large gradient maps the frequency spectrum of the input microwave signals to a position-dependent spin-flip pattern on absorption images of the cell recorded with a laser beam onto a camera. In our proof-of-principle experiment, we demonstrate a microwave spectrum analyzer that has ≈1 GHz instantaneous bandwidth centered around 13 GHz, 3 MHz frequency resolution, 2 kHz refresh rate, and a −23 dBm single-tone microwave power detection limit in 1 s measurement time. A theoretical model is constructed to simulate the image signals by considering the processes of optical pumping, microwave interaction, diffusion of Rb87 atoms, and laser absorption. We expect to reach more than 25 GHz instantaneous bandwidth in an optimized setup, limited by the applied magnetic field gradient. Our demonstration offers a practical alternative to conventional microwave spectrum analyzers based on electronic heterodyne detection. Published by the American Physical Society 2024

ICRF resonance cones in the low-density scrape-off-layer of ASDEX Upgrade

Abstract The ICRF slow wave is a potential carrier for parallel RF electric fields known to cause unwanted plasma-wall interactions in magnetic confinement fusion experiments.&amp;#xD;In nowadays machines the slow wave is usually confined to the far scrape-off layer or the limiter shadow, but conditions in future experiments and reactors may allow the slow wave to be propagative in a larger region.&amp;#xD;&amp;#xD;Simulations with RAPLICASOL for various geometries show that the ICRF slow waves appear as the so-called resonance cones characterized by large localized electric fields.&amp;#xD;The resonance cones emerge from the points along the plasma-antenna interface where (in the cold plasma approximation) the radio frequency electric field diverges.&amp;#xD;We demonstrate that in the parameter range of interest, the propagation of the resonance cones in a plasma with a density gradient is defined by a simple geometric model, using the local plasma density and the frequency as input parameters.&amp;#xD;In the context of experiments at ASDEX Upgrade, simulations illustrate that the resonance cones can emerge from a single tile of the ICRF antenna limiter.&amp;#xD;Experiments at the Ion-cyclotron System Hardware Test ARrangement (ISHTAR) were conducted to test the detection principle in a simple environment.&amp;#xD;In agreement with simulations and with predicted characteristics which depend on operation parameters, the resonance cones are excited by an RF antenna and propagate through the relatively homogeneous plasma in ISHTAR. &amp;#xD;The cones are detected at a distance from the antenna using two probes scanning through the plasma.&amp;#xD;In ASDEX Upgrade, a single tile of an antenna limiter was modified to launch RF power into a specially tailored low-density scrape-off layer.&amp;#xD;Probes at the midplane manipulator were then used to detect the wave electric fields at a distance from the RF source.&amp;#xD;The detected RF signals show that the signal maxima are located close to the lower hybrid resonance density and are highest when the source and the probes are connected along magnetic field lines.&amp;#xD;These observations agrees with the model for resonance cones from the simulations.

Elucidating the protective role of manganese seed priming in mitigating lead-induced oxidative stress: enhancements in growth, grain yield, and antioxidant activities of wheat.

Lead (Pb) is known to be extremely toxic to plants and awfully affects growth and productivity by interacting with morphological, biochemical, and physiological processes. Micronutrients are considered to reduce ion toxicity and modify various physiological processes involved in oxidative stress tolerance in plants. Hence, the limited literature about the application of micronutrients, particularly manganese (Mn), under lead stress thus demands more investigations. To sort out the role of priming treatments of Mn (1.0 and 0.1mg/L) in lead stress (200mg/kg) induced oxidative stress tolerance in wheat cultivars (Anaj-17 and Akbar-19), current experiment was designed. The experiment was arranged with completely randomized design (CRD) with three replicates. The results explored the positive role of Mn priming in strengthening the antioxidant system with increased activities of antioxidants under Pb stress. Mn priming level (0.1mg/L) significantly increased the germination percentage, germination percentage, growth traits, grain yield per plant, shoot P, shoot Ca2+, and shoot K+ while decreasing the MDA and H2O2 levels, of Anaj-17 and Akbar-19 under Pb stress (200mg/kg). Seed priming levels of Mn further upgraded the antioxidant enzymatic activities and organic osmolytes such as proline, total phenolics, flavonoids, total soluble sugars, and glycine betaine, under Pb stress. Conclusively, the 0.1mg/L level of Mn priming and Akbar-19 cultivar has proven superior in lead detoxification under Pb-induced oxidative stress. Furthermore, the outcomes revealed more accumulation of Pb in the roots of wheat than in the shoots of both wheat cultivars and emphasized the use of lower Mn levels of 0.1mg/L as the best strategy in alleviating the toxic impacts of lead in wheat. However, the conduct of large field trials is a necessity of current scenario to study the molecular aspects and associated genes contributing Pb stress tolerance with priming application of Mn and other micronutrients.

Research on motion target detection based on infrared biomimetic compound eye camera.

The cooled mid-wave infrared biomimetic compound eye camera has wide range of applications, such as industrial inspection, military project, and security. Due to the low resolution of individual eyes and the large field view of the imaging system, existing motion target enhancement and detection algorithms cannot effectively detect all potential targets. To address this issue, we propose an improved elementary motion detector model that combines a double-layer ON_OFF channel and a cross-type computational architecture, which is able to suppress a stationary background and enhance moving targets. In order to further reduce the missed detection, we designed the spatial and temporal consistency detection methods of the compound eye structure, which further improved the accuracy and stability of the detection results. The experimental results show that our method can fully utilize the features of the image and can be applied to the enhancement and detection of moving objects in complex scenes, and the detection efficiency is significantly improved.

Exoplanets across galactic stellar populations with PLATO. Estimating exoplanet yields around FGK stars for the thin disk, thick disk, and stellar halo

The vast majority of exoplanet discoveries to date have occurred around stars in the solar neighbourhood, with chemical compositions comparable to that of the Sun. However, models suggest that planetary systems in different Galactic environments, with varying dynamical histories and chemical abundances, may exhibit distinct characteristics, which can help improve our understanding of planet formation processes. This study aims to assess the potential of the upcoming PLATO mission to investigate exoplanet populations around stars in diverse Galactic environments, specifically focusing on the Milky Way thin disk, thick disk, and stellar halo. We aim to quantify PLATO's ability to detect planets in each environment and determine how these observations could constrain planet formation models. Beginning with the all-sky PLATO Input Catalogue, we kinematically classified the 2.4 million FGK stars into their respective Galactic components. For the sub-sample of stars in the long-observation LOPS2 and LOPN1 PLATO fields, we estimated planet occurrence rates using the New Generation Planet Population Synthesis (NGPPS) dataset. Combining these estimates with a PLATO detection efficiency model, we predicted the expected planet yields for each Galactic environment during a nominal 2+2 year mission. Based on our analysis, PLATO is likely to detect at least 400 exoplanets around the alpha -enriched thick disk stars. The majority of those planets are expected to be super-Earths and sub-Neptunes with radii between 2 and 10 $R_ and orbital periods between 2 and 50 days, which is ideal for studying the link between the radius valley and stellar chemistry. For the metal-poor halo, PLATO is likely to detect between 1 and 80 planets with periods between 10 and 50 days, depending on the potential existence of a metallicity threshold for planet formation. The PLATO fields contain more than 3,400 potential target stars with Fe/H &lt; -0.6, which will help improve our understanding of planets around metal-poor stars. We identified a specific target list of 47 (kinematically classified) halo stars in the high-priority, high-signal-to-noise PLATO P1 sample, offering prime opportunities in the search for planets in metal-poor environments. PLATO's unique capabilities and large field of view position it as a valuable tool for studying planet formation across the diverse Galactic environments of the Milky Way. By probing exoplanet populations around stars with a varying chemical composition, PLATO will provide helpful insights into the connection between stellar chemistry and planet formation.

112° field of view high-resolution swept-source OCT angiography for rat retinas.

This study introduces an ultra-wide field (UWF) and high-resolution swept-source optical coherence tomographic angiography (OCTA) system for rat retinal imaging. Using an asymmetrical optics design, the system achieves unprecedented details of retinal structures and vascular plexuses over a large field of view (112°) in a single-shot acquisition. Views of single-nerve fiber bundles and single capillary vessels are consistently visible over a 112° field of view. The system has a long imaging range and high penetration and allows a full view of vitreous hyaloid vessels, retina, choroid, sclera, and posterior ciliary arteries, down to sub-sclera connective tissues. In a longitudinal study of oxygen-induced retinopathy (OIR) in rats, the system successfully revealed the progression and regression of OIR-related vascular pathologies, such as ischemia, neovascularization, and tortuosity. To our knowledge, this novel UWF-OCT/OCTA prototype designed for rat retinal imaging will be a vital tool for monitoring disease progression and evaluating therapeutic interventions in preclinical models.

Research on single-point fast three-dimensional concentration reconstruction of a smoke plume based on the static interference infrared imaging spectroscopy system

To meet the requirements of real-time and effectiveness of three-dimensional concentration telemetry of gas clouds and address the difficulty of fast three-dimensional concentration reconstruction of single instrument smoke plumes, the paper proposes a single-point fast three-dimensional concentration reconstruction of the smoke plume based on a static interference infrared Fourier transform imaging spectrometer (ISIFTS) by using the advantages of high throughput, large field of view, high stability, and rapid detection. Based on the scanning field switching characteristics of ISIFTS, a single instrument quickly scans the dual-field map data to obtain the three-dimensional point cloud of the target scene. Combined with the three-dimensional spatial parameters of the scene, a multi-dimensional re-projection algorithm is constructed based on the Gaussian plume continuous diffusion model to simulate the concentration-path-length product (CL) image, and the measured CL image is solved by analyzing the smoke plume image spectra data. The normalized cross-correlation fitting algorithm is used to perform the optimal matching of simulated-measured CL images, and then the three-dimensional concentration distribution of the plume scene is reconstructed based on the dimension mapping relationship. The field smoke plume telemetry experiment was designed and carried out, and the three-dimensional concentration distribution of plume gas at three emission points in the scene was obtained. The CO2 emission rates were calculated to be 13.572 kg / s, 12.225 kg / s, and 14.114 kg / s, respectively. The data are consistent with the emission rate of the coal-fired thermal power plant, which verifies the effectiveness of the single-point fast three-dimensional concentration reconstruction of the smoke plume method based on the ISIFTS system.

Improving the polarization switching properties of wurtzite AlN by introducing IV–IV/AlN superlattice and P-doping

The large coercive electric field is the main obstacle for the application of wurtzite ferroelectrics in the memory devices. To explore the effective methods to reduce the coercive electric field of wurtzite ferroelectrics, in this work, after screening a series of possible candidates, (MC)1/(AlN)n (M = Ti, Zr) superlattices and anion P-doping are both chosen to regulate the switching energy barrier of wurtzite AlN based on the density functional theory calculations. It is found that the polarization switching energy barriers of wurtzite AlN gradually decrease by increasing the ratio of the MC (M = Ti, Zr) layer. When the ratio of the MC layer is up to 33%, the polarization switching energy barriers of (TiC)1/(AlN)n and (ZrC)1/(AlN)n are decreased by 68% and 55%, respectively, compared with that of pure wurtzite AlN. The anionic P-doping in AlN results in a 48% lower energy barrier. Also, the ferroelectric polarization in the designed superlattices and P-doped AlN is well maintained compared to pure AlN. Thus, the results show that the (MC)1/(AlN)n (M = Ti, Zr) superlattices and anion P-doping approaches are effective in improving the polarization switching properties of wurtzite AlN.

Supression of shielding effect of large area field emitter cathode in radio frequency gun environment

Abstract Utilisation of large area field emitters (LAFE) cathodes for rf gun injector hold promise for delivering compact, high power and high brightness electron beam for advanced accelerator technologies. LAFEs subjected to DC electric fields posses significant challenges due to the shielding effect which restricts emission from central emitters and decreases the overall current density. Mitigating the shielding effect of LAFE in rf gun environment is essential for meeting the desired beam quality requirement in an accelerator. The current distribution of LAFE under DC conditions depend on its various geometrical parameters such as emitter height, inter-emitter distance, aspect ratio, number of emitters. Additionally, in rf gunsetup, LAFEs are subjected to variable macroscopic electric field at different emitter position which can potentially alter the current distribution compared to DC fields. In this work, we have systematically studied the shielding effect properties of LAFE in rf gun environment under the influence of various LAFE parameters. A semi-analytical approachhas been adopted to estimate the current distribution which combines the analytically calculated field enhancement factor (γ) and numerically calculated applied rf field values. This new methodology was first validated using COMSOL simulation and then employed for field emission performance estimation of a LAFE cathode integrated in a½ cell S-band (2856 MHz) rf gun. The simulation results reveals that under favourable conditions, a Gaussian spatial distribution of beam can be obtained from LAFE thus countering the shielding effect typical in DC fields. By optimizing the LAFE parameters, the desired current and beam distribution pattern can be achieved. This study highlights the adoption of a promising approach for designing LAFE cathodes suitable for rf gun which can lead to advancement of field emission technologies for accelerator-related applications.

Evaluation of a novel forward-looking optical coherence tomography probe for endoscopic applications: an ex vivo feasibility study.

As a result of recent advances in the development of small microelectromechanical system mirrors, a novel forward-looking optical coherence tomography (OCT) probe with a uniquely large field of view is being commercially developed. The aim of this study is to prospectively assess the feasibility of this advanced OCT probe in interpreting ex vivo images of colorectal polyp tissue and to identify necessary steps for further development. A total of 13 colorectal lesions from 9 patients, removed during endoscopic resection, were imaged ex vivo with the OCT device and compared with histopathological images that served as the gold standard for diagnostics. Normal tissue from one patient, removed during the endoscopic procedure, was imaged as a negative control. We assessed the presence of features indicative for polyp type and degree of dysplasia, by comparing OCT images to histopathological images and by evaluating the presence of OCT-specific features identified by previous studies, such as effacement (loss of layered tissue structure), a hyperreflective epithelial layer, and irregularity of the surface. As verified by corresponding histological images, tissue structures such as blood vessels and tissue layers could be distinguished in OCT images of the normal tissue sample. Detailed structures on histological images such as crypts and cell nuclei could not be identified in the OCT images. However, we did identify OCT features specific for colorectal lesions, such as effacement and a hyperreflective epithelial layer. In general, the imaging depth was about 1mm. Some relevant tissue structures could be observed in OCT images of the novel device. However, some adaptations, such as increasing imaging depth using a laser with a longer central wavelength, are required to improve its clinical value for the imaging of colorectal lesions.

Implementation of entropically secure encryption: Securing personal health data

AbstractEntropically secure encryption (ESE) offers unconditional security with shorter keys compared to the One‐Time Pad. Here, the first implementation of ESE for bulk encryption is presented. The main computational bottleneck for bulk ESE is a multiplication in a very large finite field. This involves multiplication of polynomials followed by modular reduction. A polynomial multiplication is implemented based on the gf2x library, with modifications that avoid inputs of vastly different length, thus improving speed. Additionally, a recently proposed efficient reduction algorithm that works for any polynomial degree is implemented. Two use cases are investigated: x‐ray images of patients and human genome data. Entropy estimation is conducted using compression methods whose results determine the key lengths required for ESE. The running times for all steps of the encryption are reported. The potential of ESE to be used in conjunction with quantum key distribution (QKD), in order to achieve full information‐theoretic security of QKD‐protected links for these use cases is discussed.

Mapping AGN winds: A connection between radio-mode AGNs and the AGN feedback cycle

We present a kinematic analysis based on the large integral field spectroscopy (IFS) dataset of SDSS-IV MaNGA (Sloan Digital Sky Survey/Mapping Nearby Galaxies at Apache Point Observatory; ∼10 000 galaxies). We have compiled a diverse sample of 594 unique active galactic nuclei (AGNs), identified through a variety of independent selection techniques, encompassing radio (1.4 GHz) observations, optical emission-line diagnostics (BPT), broad Balmer emission lines, mid-infrared colors, and hard X-ray emission. We investigated how ionized gas kinematics behave in these different AGN populations through stacked radial profiles of the [O III] 5007 emission-line width across each AGN population. We contrasted AGN populations against each other (and non-AGN galaxies) by matching samples by stellar mass, [O III] 5007 luminosity, morphology, and redshift. We find similar kinematics between AGNs selected by BPT diagnostics compared to broad-line-selected AGNs. We also identify a population of non-AGNs with similar radial profiles as AGNs, indicative of the presence of remnant outflows (or fossil outflows) of past AGN activity. We find that purely radio-selected AGNs display enhanced ionized gas line widths across all radii. This suggests that our radio-selection technique is sensitive to a population in which AGN-driven kinematic perturbations have been active for longer durations (potentially due to recurrent activity) than in purely optically selected AGNs. This connection between radio activity and extended ionized gas outflow signatures is consistent with recent evidence that suggests radio emission (expected to be diffuse) originated due to shocks from outflows. We conclude that different selection techniques can trace different AGN populations not only in terms of energetics but also in terms of AGN evolutionary stages. Our results are important in the context of the AGN duty cycle and highlight integral field unit data’s potential to deepen our knowledge of AGNs and galaxy evolution.

Manipulating microfluidic freezing phenomena of electrolytes using electromagnetic stimuli

We investigate the transients of freezing of a flowing electrolyte between cold microfluidic domain walls. We explore the novel effect of morphing the solidification characteristics of the flow system using externally applied electric and magnetic fields. The spatiotemporal evolution of solid–liquid (S–L) interface is simulated using arbitrary Lagrangian–Eulerian approach. We show that the solidification rate is highly influenced by advection effects, and for increasingly high liquid flow rates, solidification stops way before the event of channel closure. Due to electro-magneto-hydrodynamic interactions, a substantial decrease in channel closing time is observed with imposed fields. However, a considerably large electric field may lead to a significant increase in Joule heating, which marginally increases the channel closing time. The magnetic field is observed to produce smoother, curved frozen layers. The electric field tends to enhance the solidification rates more uniformly along the channel length, resulting in much flatter S–L front, hence trapping lesser liquid at channel closure. The results reveal that freezing kinetics in microfluidic devices can be morphed by using electric and magnetic fields, governed by the electric field number (En) and Hartmann number (Ha). The findings may be crucial for phase-change based microfluidic-systems, micro-castings, flow freezing valves, and diodes.

Space Weather Forecasts of Ground Level Space Weather in the UK: Evaluating Performance and Limitations

AbstractGeomagnetically Induced Currents (GICs) are a severe space weather hazard, driven through coupling between the solar wind and magnetosphere. GICs are rarely measured directly, instead the ground magnetic field variability is often used as a proxy. Recently space weather models have been developed to forecast whether the magnetic field variability (R) will exceed specific, extreme thresholds. We test an example machine learning‐based model developed for the northern United Kingdom. We evaluate its performance (discriminative skill and calibration) as a function of magnetospheric state, solar wind input and magnetic local time. We find that the model's performance is highest during active conditions, for example, geomagnetic storms, and lowest during isolated substorms and “quiet” intervals, despite these conditions dominating the training data set. Correspondingly, the performance is high when the solar wind conditions are elevated (i.e., high velocity, large total magnetic field strength, and the interplanetary magnetic field oriented southward), and at a minimum when the north‐south component of the magnetic field is highly variable or around zero. Regarding magnetic local time, performance is highest within the dusk and night sectors, and lowest during the day. The model appears to capture multiple modes of magnetospheric activity, including substorms and viscous interactions, but poorly predicts impulsive phenomena (i.e., storm sudden commencements) and longer timescale coupling processes. Future models of mid‐latitude magnetic field variability will need to effectively use longer time intervals of unpropagated (i.e., observations from L1) solar wind to more completely describe the magnetospheric conditions and response.