Large Field Research Articles

High-Temperature (Cu,C)Ba2Ca3Cu4Oy Superconducting Films with Large Irreversible Fields Grown on SrLaAlO4 Substrates by Pulsed Laser Deposition

(Cu,C)Ba2Ca3Cu4Oy is a nontoxic cuprate superconducting material with a superconducting transition temperature of about 116 K. Recently, it was found that bulk samples of this material synthesized under high pressure hold the highest irreversibility line among all the superconductors, which is very promising for its application in the liquid nitrogen temperature field. In this work, high-temperature (Cu,C)Ba2Ca3Cu4Oy superconducting films with large irreversible fields were prepared on SrLaAlO4(00l) substrates by pulsed laser deposition. The substrate temperature during deposition proved to be the most important parameter determining the morphology and critical temperature of the superconductors, with 680 °C considered to be the optimum temperature. X-ray diffraction (XRD) results showed that the (Cu,C)Ba2Ca3Cu4Oy films prepared under optimal conditions exhibited epitaxial growth with the a-axis perpendicular to the film surface and the b- and c-axes parallel to the substrate, with no evidence of any other orientation. In addition, resistivity measurements showed that the onset transition temperature (Tconset) was approximately 116 K, the zero-resistance critical temperature (Tc0) was around 53 K, and the irreversible field (Hirr) was about 9 T at 37 K for (Cu,C)Ba2Ca3Cu4Oy films under optimal temperature. This is the first example of the successful growth of superconducting (Cu,C)Ba2Ca3Cu4Oy films on SrLaAlO4(00l) substrates. This will facilitate high-performance applications of (Cu,C)Ba2Ca3Cu4Oy superconducting materials in the liquid nitrogen temperature field.

Overlapping top gate electrodes based on low temperature atomic layer deposition for nanoscale ambipolar lateral junctions

We present overlapping top gate electrodes for the formation of gate defined lateral junctions in semiconducting layers as an alternative to the back gate/top gate combination and to the split gate configuration. The optical lithography microfabrication of the overlapping top gates is based on multiple layers of low-temperature atomic layer deposited hafnium oxide, which acts as a gate dielectric and as a robust insulating layer between two overlapping gate electrodes exhibiting a large dielectric breakdown field of >1×109V m−1 . The advantage of overlapping gates over the split gate approach is confirmed in model calculations of the electrostatics of the gate stack. The overlapping gate process is applied to Hall bar devices of mercury telluride in order to study the interaction of different quantum Hall states in the nn′, np, pn and pp′ regime.

Fe(Se,Te) Thin Films Deposited through Pulsed Laser Ablation from Spark Plasma Sintered Targets

Iron-based superconductors are under study for their potential for high-field applications due to their excellent superconducting properties such as low structural anisotropy, large upper critical fields and low field dependence of the critical current density. Between them, Fe(Se,Te) is simple to be synthesized and can be fabricated as a coated conductor through laser ablation on simple metallic templates. In order to make all the steps simple and fast, we have applied the spark plasma sintering technique to synthesize bulk Fe(Se,Te) to obtain quite dense polycrystals in a very short time. The resulting polycrystals are very well connected and show excellent superconducting properties, with a critical temperature onset of about 16 K. In addition, when used as targets for pulsed laser ablation, good thin films are obtained with a critical current density above 105 A cm−2 up to 16 T.

Cysteine-induced growth of jagged gold bipyramids from penta-twinned nanorod seeds.

The understanding on the growth mechanism of complex gold nanostructures both experimentally and theoretically can guide their design and fabrication toward various applications. In this work, we report a cysteine-directed overgrowth of penta-twinned nanorod seeds into jagged gold bipyramids with discontinuous stepped {hhk} facets. By monitoring the growth process, we find that {hhk} facets with large k/h values (∼7) are formed first at two ends of the nanorods, followed by the protrusion of the middle section exposing {hhk} facets with smaller indices (k/h ∼ 2-3). Molecular dynamics simulations indicate that the strong adsorption of cysteine molecules on {110} facets is likely responsible for the formation of stepped {hhk} facets, and the stronger adsorption of cysteine molecules on {hhk} facets with smaller k/h compared to that on {hhk} facets with larger k/h is a possible cause of the discontinuity of {hhk} facets at the middle of gold bipyramids. The obtained jagged gold bipyramids display large field enhancement under illumination due to their sharp nanostructures, demonstrating their application potentials in surface-enhanced spectroscopy and catalysis.

Design of Lidar Receiving Optical System with Large FoV and High Concentration of Light to Resist Background Light Interference

Lidar has the advantages of high accuracy, high resolution, and is not affected by sunlight. It has been widely used in many fields, such as autonomous driving, remote sensing detection, and intelligent robots. However, the current lidar detection system belongs to weak signal detection and generally uses avalanche photoelectric detector units as detectors. Limited by the current technology, the photosensitive surface is small, the receiving field of view is limited, and it is easy to cause false alarms due to background light. This paper proposes a method based on a combination of image-side telecentric lenses, microlens arrays, and interference filters. The small-area element detector achieves the high-concentration reception of echo beams in a large field of view while overcoming the interference of ambient background light. The image-side telecentric lens realizes that the center lines of the echo beams at different angles are parallel to the central axis, and the focus points converge on the same focal plane. The microlens array collimates the converged light beams one by one into parallel light beams. Finally, a high-quality aspherical focusing lens is used to focus the light on the small-area element detector to achieve high-concentration light reception over a large field of view. The system achieves a receiving field of view greater than 40° for a photosensitive surface detector with a diameter of 75 μm and is resistant to background light interference.

A light-weight rectangular decomposition large kernel convolution network for deformable medical image registration

The performance and speed of medical image registration have been greatly boosted by advanced deep-learning based methods. However, most current methods are challenged by large deformations between input images, which necessitate a compromise in computational cost to enhance the model’s receptive field and its ability to model long-range spatial relationships for improving registration performance. In order to enhance the performance of registration for images with large deformations at a lower computational cost, in this paper, we propose a light-weight registration model with the ability to model large receptive fields and long-range spatial relationships, named LL-Net. The core components of LL-Net consist of a Rectangular Decomposition Large Kernel Attention (RD-LKA) layer and a Spatial and Channel Fusion Attention (SC-Fusion) layer. The RD-LKA layer utilizes anisotropic depth-wise large kernel convolutions to capture large receptive fields with an extremely low parameter count while modeling long-range spatial relationships. Moreover, the SC-Fusion layer enhances the model’s feature fusion capability and strengthens feature representations at critical locations. Our LL-Net exhibits state-of-the-art performance across multiple datasets. Specifically, it achieves a Dice score of 76.7% and an HD95 of 2.983 mm on the IXI dataset, and a Dice score of 87.8% and an HD95 of 1.042 mm on the OASIS dataset. Experimental results substantiate the efficacy of LL-Net in capturing large receptive fields and modeling long-range spatial relationships. The code for LL-Net is available at https://github.com/BoyOfChu/LL_Net.

A Human-Scale Clinically Ready Electromagnetic Navigation System for Magnetically Responsive Biomaterials and Medical Devices.

Magnetic navigation systems are used to precisely manipulate magnetically responsive materials enabling the realization of new minimally invasive procedures using magnetic medical devices. Their widespread applicability has been constrained by high infrastructure demands and costs. The study reports on a portable electromagnetic navigation system, the Navion, which is capable of generating a large magnetic field over a large workspace. The system is easy to install in hospital operating rooms and transportable through health care facilities, aiding in the widespread adoption of magnetically responsive medical devices. First, the design and implementation approach for the system are introduced and its performance is characterized. Next, in vitro navigation of different microrobot structures is demonstrated using magnetic field gradients and rotating magnetic fields. Spherical permanent magnets, electroplated cylindrical microrobots, microparticle swarms, and magnetic composite bacteria-inspired helical structures are investigated. The navigation of magnetic catheters is also demonstrated in two challenging endovascular tasks: 1) an angiography procedure and 2) deep navigation within the circle of Willis. Catheter navigation is demonstrated in a porcine model in vivo to perform an angiography under magnetic guidance.

Data Lake Conceptualized Web Platform for Food Research Data Collection

Food research is uniquely intertwined with everyday life and necessitates the utilization of big data. Within this domain, the research data consist of various forms and formats, encompassing biological experiment results, chemical analysis data, nutritional information, microbiological data, sensor data, images, and videos. This diversity stems from the integration of data from various subdomains within the larger field. With recent advancements in deep learning technology, the importance of data has grown significantly, resulting in increased reliance on data-driven research. Although specialized platforms for sharing and utilizing data have been established at the national level, particularly in the bioscience field, food research lacks a dedicated infrastructure and specialized data-sharing platforms. In this study, we develop a platform that leverages Hadoop-based distributed file systems to create a data lake. This platform enables data storage and sharing through a web-based interface. The distributed file system supports scalability by adding data nodes, making it an effective solution for capacity expansion. In addition, the web-based platform ensures high accessibility, allowing users access from anywhere, at any time, using any device. Finally, we introduce the establishment of a 1.8 PB Hadoop-based physical storage system and present an approach for building a highly accessible web platform with substantial utility.

Neuromorphic Computing in Synthetic Antiferromagnets by Spin‐Orbit Torque Induced Magnetic‐Field‐Free Magnetization Switching

AbstractSynthetic antiferromagnet (SAF) with high thermal stability, ultra‐fast spin dynamics, and highly efficient spin‐orbit torque switching has great application potential in neuromorphic computing hardware. However, two challenges, the weakening of Hall signal in the remanent state and the need for a large auxiliary magnetic field for perpendicular magnetization switching, greatly limit the advantages of SAF in neuromorphic computing. In this work, both the enhanced anomalous Hall resistance and magnetic‐field‐free perpendicular magnetization switching are achieved by using oblique sputtering to fabricate the Pt/CoPt/Ru/CoTb SAF with strong interlayer exchange coupling and magnetic moment compensation. The fabricated SAF as synapse shows nearly linear, nonvolatile multistate plasticity, and as neuron exhibits a nonlinear sigmoid activation function, which are used to construct a fully connected neural network with a remarkable 97.0–98.1% recognition rate for the handwritten digits. Additionally, SAF serving as spike‐timing‐dependent plasticity synapse is used to construct an adaptive, unsupervised learning spiking neural network, and achieve an 87.0% accuracy in handwritten digit recognition. The findings exhibit the promise of SAFs as specialized hardware for high‐performance neuromorphic computing, offering high recognition rates and low power consumption.

Solar multiobject multiframe blind deconvolution with a spatially variant convolution neural emulator

The study of astronomical phenomena through ground-based observations is always challenged by the distorting effects of Earth's atmosphere. Traditional methods of post facto image correction, essential for correcting these distortions, often rely on simplifying assumptions that limit their effectiveness, particularly in the presence of spatially variant atmospheric turbulence. Such cases are often solved by partitioning the field of view into small patches, deconvolving each patch independently, and merging all patches together. This approach is often inefficient and can produce artifacts. Recent advancements in computational techniques and the advent of deep learning offer new pathways to address these limitations. This paper introduces a novel framework leveraging a deep neural network to emulate spatially variant convolutions, offering a breakthrough in the efficiency and accuracy of astronomical image deconvolution. By training on a dataset of images convolved with spatially invariant point spread functions and validating its generalizability to spatially variant conditions, this approach presents a significant advancement over traditional methods. The convolution emulator is used as a forward model in a multiobject multiframe blind deconvolution algorithm for solar images. The emulator enables the deconvolution of solar observations across large fields of view without resorting to patch-wise mosaicking, thus avoiding the artifacts associated with such techniques. This method represents a significant computational advantage, reducing processing times by orders of magnitude.

First records of a new Europe’s southernmost glacier found in Southern Albania

Several perennial snow and ice bodies have been recently studied and monitored in three mountain massifs across the Balkan Peninsula: Prokletije (Northern Albania), Durmitor (Montenegro) and Pirin (Bulgaria), the two glacierets in the Pirin Mountains until soon considered as southernmost of their kind in Europe. In September 2022 a relatively large snow field (about 1.5 ha) was discovered and described for a first time in the glacial cirque Gryka e Kazanit in the Nëmerçka Mountains of Southern Albania. The snow accumulation lies on 1550–1650 m a.s.l. below a vertical limestone cliff with a height of almost 1000 m. The site was visited again in November 2023, when the snow field diminished its size to less than 1 ha. At the same time, multi-annual firn layers were exposed under the last year snow, with depth at least several metres, and indications were observed of ice, buried in the debris cover below. Newest findings indicate that the studied snow-firn body is a glacieret similar to those found in the Pirin Mountains. On a longer-term, nine perennial snow/firm bodies on the Balkans resemble small glaciers rather than snow and ice patches at least under current climatic conditions. Situated on 40°08′ Northern latitude, the newly discovered Nemërçka Glacieret is nominated to be the southernmost glacier in Europe.

Challenges in the Planning, Construction and Farming Practices in Agrivoltaic Systems With Vertically Mounted Panels

Several challenges in planning, construction, and farming practices hinder the optimization of agrivoltaic systems (AS) and the achievement of optimal crop production. This paper identifies and addresses these issues while presenting initial solutions. One specific type of AS involves vertically mounted panels on arable or grassland sites. The installation of panel rows divides large fields into narrow units, restricting the use of farming implements with different working widths. Implement widths must align with the spacing between panel rows, which often results in residual strips or overlapping issues when field operations are carried out. Furthermore, boundary effects in AS are more pronounced, impacting yield along field borders. The presence of panel rows also complicates driving operations, requiring reduced speeds and posing collision risks between implements and panels. Soil compaction during AS construction, microclimate variations, and panel contamination by dust, or spray drift deposits further affect plant growth and solar system performance. Initial solutions are proposed to address these challenges. These include careful planning of row spacing based on the working widths of critical implements such as combines, adoption of field sprayers with foldable booms, consideration of pneumatic fertilizer spreaders, and integration of precision farming techniques to manage variability within AS. Additionally, the use of construction machinery with low soil pressure, employment of steering technologies based on global navigation satellite systems, and research on panel cleaning devices are suggested. Overall, this paper highlights the need for further research and development to overcome farming challenges in agrivoltaic systems with vertically mounted panels.

Fate and transport of viable bacillus anthracis simulant spores in ambient air during a large outdoor decontamination field exercise.

Following an incident involving a release of Bacillus anthracis spores or other biological threat agent into the outdoor environment, understanding the factors that may affect the bioagent's fate and transport can help predict viable contaminant spread via the ambient air. This article provides scientific data for the first time on ambient air concentrations of bacterial spores over time and location during different phases of a field test in which Bacillus atrophaeus (surrogate for B. anthracis) spores were released outdoors as part of a full-scale study on sampling and decontamination in an urban environment. This study advances the knowledge related to the fate and transport of bacterial spores (such as those causing anthrax disease) as an aerosol in the outdoor environment over the course of three weeks in a mock urban environment and has exposure and health risk implications. The highest spore air concentrations occurred at the beginning of the study (e.g. during inoculation of surfaces and characterization sampling), and in the downwind direction, but diminished over time; few B. atrophaeus spores were detected in the air after several weeks and following decontamination. Therefore, in an actual incident, potential reaerosolization of the microorganism and subsequent transport in the air during surface sampling and remediation efforts should be considered for determining exclusion zone locations and estimating potential risk to neighboring communities. The data also provide evidence suggesting that the large-scale decontamination of outdoor surfaces may reduce air concentrations of the bioagent, which is important since exposure of B. anthracis via inhalation is a primary concern.

All-in-Focus Three-Dimensional Reconstruction Based on Edge Matching for Artificial Compound Eye

An artificial compound eye consists of multiple apertures that allow for a large field of view (FOV) while maintaining a small size. Each aperture captures a sub-image, and multiple sub-images are needed to reconstruct the full FOV. The reconstruction process is depth-related due to the parallax between adjacent apertures. This paper presents an all-in-focus 3D reconstruction method for a specific type of artificial compound eye called the electronic cluster eye (eCley). The proposed method uses edge matching to address the edge blur and large textureless areas existing in the sub-images. First, edges are extracted from each sub-image, and then a matching operator is applied to match the edges based on their shape context and intensity. This produces a sparse matching result that is then propagated to the whole image. Next, a depth consistency check and refinement method is performed to refine the depth of all sub-images. Finally, the sub-images and depth maps are merged to produce the final all-in-focus image and depth map. The experimental results and comparative analysis demonstrate the effectiveness of the proposed method.

Free-breathing high-resolution respiratory-gated radial stack-of-stars magnetic resonance imaging of the upper abdomen at 7 T.

Ultrahigh field magnetic resonance imaging (MRI) (≥ 7 T) has the potential to provide superior spatial resolution and unique image contrast. Apart from radiofrequency transmit inhomogeneities in the body at this field strength, imaging of the upper abdomen faces additional challenges associated with motion-induced ghosting artifacts. To address these challenges, the goal of this work was to develop a technique for high-resolution free-breathing upper abdominal MRI at 7 T with a large field of view. Free-breathing 3D gradient-recalled echo (GRE) water-excited radial stack-of-stars data were acquired in seven healthy volunteers (five males/two females, body mass index: 19.6-24.8 kg/m2) at 7 T using an eight-channel transceive array coil. Two volunteers were also examined at 3 T. In each volunteer, the liver and kidney regions were scanned in two separate acquisitions. To homogenize signal excitation, the time-interleaved acquisition of modes (TIAMO) method was used with personalized pairs of B1 shims, based on a 23-s Cartesian fast low angle shot(FLASH) acquisition. Utilizing free-induction decay navigator signals, respiratory-gated images were reconstructed at a spatial resolution of 0.8 × 0.8 × 1.0 mm3. Two experienced radiologists rated the image quality and the impact of B1 inhomogeneity and motion-related artifacts on multipoint scales. The images of all volunteers showcased effective water excitation and were accurately corrected for respiratory motion. The impact of B1 inhomogeneity on image quality was minimal, underscoring the efficacy of the multitransmit TIAMO shim. The high spatial resolution allowed excellent depiction of small structures such as the adrenal glands, the proximal ureter, the diaphragm, and small blood vessels, although some streaking artifacts persisted in liver image data. In direct comparisons with 3 T performed for two volunteers, 7-T acquisitions demonstrated increases in signal-to-noise ratio of 77% and 58%. Overall, this work demonstrates the feasibility of free-breathing MRI in the upper abdomen at submillimeter spatial resolution at a magnetic field strength of 7 T.

Comprehensive review of hydrothermal liquefaction data for use in machine‐learning models

AbstractHydrothermal liquefaction is a new, sustainable pathway to generate biogenic liquids from organic resources. The technology is compatible with a wide variety of resources such as lignocellulosic resources, organic waste, algae, and sewage sludge. The chemistry is complex and predictions of yields are notoriously difficult. Understanding and modeling of hydrothermal liquefaction is currently mostly based on a simplified biochemical analysis and product yield data. This paper presents a large dataset of 2439 experiments in batch reactors that were extracted from 171 publications in the scientific literature. The data include biochemical composition data such as fiber content and composition, proteins, lipids, carbohydrates, and ash. The experimental conditions are recorded for each experiment as well as the reported yields. The objective of this paper is to make a large database available to the scientific community. This database is analyzed with machine‐learning tools. The results show that there is no consensus on the analysis techniques, experimental procedures, and reported data. There are many inconsistencies across the literature that should be improved by the scientific community. Machine‐learning tools with a large dataset allow the generation of reliable yield production tools with a large application field. Given the accuracy of the data, the overall precision of prediction in an extrapolation to new results can be expected to be around 10%.

Massive, long-lived electrostatic potentials in a rotating mirror plasma

Hot plasma is highly conductive in the direction parallel to a magnetic field. This often means that the electrical potential will be nearly constant along any given field line. When this is the case, the cross-field voltage drops in open-field-line magnetic confinement devices are limited by the tolerances of the solid materials wherever the field lines impinge on the plasma-facing components. To circumvent this voltage limitation, it is proposed to arrange large voltage drops in the interior of a device, but coexist with much smaller drops on the boundaries. To avoid prohibitively large dissipation requires both preventing substantial drift-flow shear within flux surfaces and preventing large parallel electric fields from driving large parallel currents. It is demonstrated here that both requirements can be met simultaneously, which opens up the possibility for magnetized plasma tolerating steady-state voltage drops far larger than what might be tolerated in material media.

Observation of mammalian living cells with femtosecond single pulse illumination generated by a soft X-ray free electron laser

Soft X-ray transmission microscopy is a powerful tool for visualizing cellular structures due to the natural contrast between organic material and water, but radiation damage has hindered its application to living cells. We have developed a soft X-ray microscope using femtosecond pulse illumination generated by a soft X-ray free electron laser, with which structural change of cells caused by radiation damage is negligible. Employing Wolter mirrors for illumination and objective optics allowed us to perform soft X-ray imaging with a large field of view, enabling observation of mammalian cells. We successfully captured images of living cells in a culture medium visualizing their carbon distribution. The broad wavelength-tunability of soft X-ray free electron lasers, in conjunction with the achromaticity of Wolter mirrors, enabled wavelength resolved cellular imaging.

Strain-driven high energy storage in BaTiO3-based lead-free epitaxial thin films

In this work, the epitaxial 0.85BaTiO3-0.15Bi(Mg1/2Ti1/2)O3 (BT-BMT) films with large compressive strain were fabricated on SrTiO3 (001). The expansion of the unit cell volume and out-of-plane lattice parameter and the large built-in electric field (Ebi) in BT-BMT films indicate the existence of defect dipoles. It was found that the polarization and the breakdown strength can be optimized by the strain and the defects, respectively. Ultimately, a desirable energy density of 90.3 J/cm3 with efficiency of 62.3% was achieved. It suggests that strain can serve as a practical means to modulate the energy storage performance of ferroelectric epitaxial film capacitors.

The dominance and growth of shallow groundwater resources in continuous permafrost environments

Water is a limited resource in Arctic watersheds with continuous permafrost because freezing conditions in winter and the impermeability of permafrost limit storage and connectivity between surface water and deep groundwater. However, groundwater can still be an important source of surface water in such settings, feeding springs and large aufeis fields that are abundant in cold regions and generating runoff when precipitation is rare. Whether groundwater is sourced from suprapermafrost taliks or deeper regional aquifers will impact water availability as the Arctic continues to warm and thaw. Previous research is ambiguous about the role of deep groundwater, leading to uncertainty regarding Arctic water availability and changing water resources. We analyzed chemistry and residence times of spring, stream, and river waters in the continuous permafrost zone of Alaska, spanning the mountains to the coastal plain. Water chemistry and age tracers show that surface waters are predominately sourced from recent precipitation and have short (<50 y) subsurface residence times. Remote sensing indicates trends in the areal extent of aufeis over the last 37 y, and correlations between aufeis extent and previous year summer temperature. Together, these data indicate that surface waters in continuous permafrost regions may be impacted by short flow paths and shallow suprapermafrost aquifers that are highly sensitive to climatic and hydrologic change over annual timescales. Despite the lack of connection to regional aquifers, continued warming and permafrost thaw may promote deepening of the shallow subsurface aquifers and creation of shallow taliks, providing some resilience to Arctic freshwater ecosystems.