Multilayer Structure Research Articles

Brazing Zircaloy-4 to Ti3AlC2 using Ti–Zr–Cu–Ni amorphous alloys: Microstructural evolution and mechanical properties

Brazing of Zircaloy-4 (Zr-4) to Ti3AlC2 ceramic was investigated using a Ti–13Zr–21Cu–9Ni (wt.%) amorphous braze alloy (ABA) at temperatures ranging from 840 °C to 990 °C for 5 min. The interfacial reactions of the brazed joint were comprehensively analyzed, revealing a distinct multilayer structure consisting of Ti3AlC2/ZrC/α-Zr(Ti) + [Zr(Ti)]2Cu + [Zr(Ti)]2[Cu(Ni)]/α-Zr(Ti)/α-Zr. The formation of the ZrC carbide particle layer primarily results from the reaction between the molten ABA and decomposed Ti3AlC2 caused by the de-intercalation of Al. Additionally, the dissolution of Zr-4 into the ABA induces an alteration in the composition of the Zr-4/ABA interface, leading to the formation of α-Zr(Ti) isothermal solidification dendrites. The effect of brazing temperature on the mechanical properties of the joint was investigated and detailed fracture analysis was conducted to determine the failure mechanism. The fracture path result indicated that the joint primarily fractured within the ZrC layer due to the mismatch of hardness, rather than within the reticular [Zr(Ti)]2[Cu(Ni)] segregation phase. The maximum shear strength of the brazed Ti3AlC2/Zr-4 joint with an average strength of 187 ± 34 MPa was achieved by brazing at 930 °C for just 5 min. With the increase in brazing temperature, the thickness of the ZrC ceramic layer became thicker in an undulating manner, and the content of Zr-based alloy particles in the ZrC layer increased gradually, resulting in a slight decrease in the bearing capacity of the joint. The presented results provide valuable insights into the microstructural evolution, interfacial reactions, and mechanical properties of the Ti3AlC2/Zr-4 brazed joints using amorphous alloys.

Research on accident early warning of metallurgical enterprises based on grey DEMATEL/ISM and Bayesian network

To clarify the complex relationship between the factors causing safety accidents in metallurgical enterprises and predict the risk of accidents in enterprises, a correlation analysis model of the factors causing safety accidents in metallurgical enterprises based on grey Decision-Making Trial and Evaluation Laboratory/Interpretative Structural Modeling (DEMATEL/ISM) was established, and a Bayesian network early warning model was constructed on this basis. The relationship and action path of accident-causing factors in metallurgical enterprises were clarified. The factors were hierarchically divided and a multi-layer hierarchical structure model was established to obtain the neighboring cause, transitional cause, and essential cause of the accident. The results showed that the employee violation rate, the hazardous substances reserves, the toxic gas and dust pollution control compliance rate, the pass rate for equipment maintenance, and the qualification rate of special equipment were the neighboring causes of the accident. The perfection of the safety production management system was the essential cause. The Bayesian network early warning model was applied to the Fuxin Jiuxing Titanium work site. The expected risk probability of an accident was 17.9%, which was in a comparatively safe state (State2). The results obtained by the Bayesian model are consistent with those obtained by AHP and fuzzy comprehensive evaluation method, which proved the accuracy of the early warning model. The Bayesian model can give the risk probability value of the accident and the risk probability value of the accident cause factors at the same time, and include the causal relationship and conditional correlation relationship among the indicator variables in the reasoning process, which can provide targeted technical support for the construction of the emergency system of risk classification management and control.

Core-Shell Interface Engineering Strategies for Modulating Energy Transfer in Rare Earth-Doped Nanoparticles.

Rare earth-doped nanoparticles (RENPs) are promising biomaterials with substantial potential in biomedical applications. Their multilayered core-shell structure design allows for more diverse uses, such as orthogonal excitation. However, the typical synthesis strategies-one-pot successive layer-by-layer (LBL) method and seed-assisted (SA) method-for creating multilayered RENPs show notable differences in spectral performance. To clarify this issue, a thorough comparative analysis of the elemental distribution and spectral characteristics of RENPs synthesized by these two strategies was conducted. The SA strategy, which avoids the partial mixing stage of shell and core precursors inherent in the LBL strategy, produces RENPs with a distinct interface in elemental distribution. This unique elemental distribution reduces unnecessary energy loss via energy transfer between heterogeneous elements in different shell layers. Consequently, the synthesis method choice can effectively modulate the spectral properties of RENPs. This discovery has been applied to the design of orthogonal RENP biomedical probes with appropriate dimensions, where the SA strategy introduces a refined inert interface to prevent unnecessary energy loss. Notably, this strategy has exhibited a 4.3-fold enhancement in NIR-II in vivo imaging and a 2.1-fold increase in reactive oxygen species (ROS)-related photodynamic therapy (PDT) orthogonal applications.

Interconnectedness between Islamic and conventional banks: a multilayer network view

PurposeThis study aims to examine information (stock return, volatility and extreme risk) spillovers and interconnectedness within dual-banking systems.Design/methodology/approachUsing multilayer information spillover networks, this paper conduct a deep analysis of contagion dynamics among 24 Islamic and 46 conventional banks from 2006 to 2022.FindingsThe findings show the network’s rapid response to financial shocks. Through cross-sector analysis, this paper identify information spillovers between and within Islamic and conventional banking systems. Furthermore, this research illustrates distinct roles played by Islamic and conventional banks within the multilayer network structure, contingent upon the nature of the financial shock.Practical implicationsUnderstanding the differential roles of Islamic and conventional banks in information transmission can aid policymakers and financial institutions in devising more effective risk management strategies, thereby enhancing financial stability within dual-banking systems.Originality/valueThis study contributes to the literature by emphasizing the necessity of examining contagion mechanisms beyond traditional single-layer network structures, shedding light on the shadow dynamics of information transmission in dual-banking systems.

Multi-layered medium ultrasonic phased array sparse TFM imaging based on self-adaptive differential evolution algorithm

Abstract Multilayer Composite material structures have been widely used in modern engineering fields. However, defects within these materials can adversely affect mechanical properties. Ultrasonic phased array total focusing method (TFM) imaging has advantages of high precision and dynamic focusing over the entire range, achieving significant progress in homogeneous medium detection. However, heavy computational burdens of multilayer structures lead to inefficient imaging. To address this issue, a sparse-TFM imaging algorithm using ultrasonic phased arrays suitable for multilayer media is proposed in this paper. This method constructs a fitness function with constraints such as main lobe width and sidelobe peak. Its objective is to obtain the distribution of sparse array element positions using an self-adaptive differential evolution algorithm. Subsequently, the delay time of each array element in multilayer media sparse TFM is calculated using the root mean square (RMS) principle and combined with amplitude weighting, the method corrects the imaging results. Compared with the Ray-based full-matrix capture and TFM method (Ray-based FMC/TFM), the RMS-based full-matrix capture and TFM (RMS-based FMC/TFM), and the phase shift method, the experimental and simulation results demonstrate that the proposed method significantly reduces the imaging data volume, improves computational efficiency, and maintains quantitative errors within 0.2 mm.

In-situ interconnected 1D/2D/3D architectures of CNT/MoS2/Fe3O4 membranes for increasing degradation efficiency of penetrative electro-Fenton under low energy consumption

The electro-Fenton oxidation process for the degradation of organic pollutants in recalcitrant wastewater has garnered significant attention and research efforts in the field of advanced water treatment. This is primarily due to its highly effective degradation capabilities and the advantages it offers, including the avoidance of unsafe transportation and storage of hydrogen peroxide (H2O2). However, challenges such as relatively high energy consumption, complex operational requirements, and limited operational stability continue to pose significant economic constraints on the widespread application of electro-Fenton technology in water purification. In this study, we employed a secondary hydrothermal method to construct a multi-layered CNT/MoS2/Fe3O4 composite heterostructure in situ. Leveraging the synergistic effects of the introduced variable valence elements, Fe and Mo, and the interconnected multi-layered membrane structure, the CNT/MoS2/Fe3O4 electro-Fenton membrane holds promise in a permeable filtration system. Under the conditions of a current density of 1.50 mA/cm² and an electrolyte concentration of 0.50 mol/L, the CNT/MoS2/Fe3O4 composite membrane exhibited a degradation efficiency of over 90.00 % for 100.00 mg/L RhB within 10 minutes, and the degradation rate approached nearly 99.00 % at 60 minutes. Furthermore, the degradation efficiency for various recalcitrant organic dye wastewaters, including phenol, methyl orange, and methylene blue, could be maintained at levels ranging from 80.00 % to 97.00 %. Particularly, under optimized operating conditions, the specific energy consumption (EC) for the CNT/MoS2/Fe3O4 membrane process was measured at 0.60±0.01 kWh/m³, showcasing exceptionally low energy consumption characteristics. In conclusion, it is expected to contribute to the reduction of the overall consumption of heterogeneous electro-Fenton oxidation systems and enhance their operational efficiency. This innovative approach represents a significant advancement in the field, offering the potential to address the economic limitations associated with electro-Fenton technology in water quality purification.

Control of work functions of nanophotonic components

Work function is an essential material’s property playing important roles in electronics, photovoltaics, and more recently, in nanophotonics. We have studied effects of organic, and inorganic dielectric materials on work functions of Au films in single layered, and multilayered structures. We found that measured work function of metallic surfaces can be affected by dielectric materials situated 10–100 nm away from the metallic surface. We have found that, (i) the glass underneath ~ 50 nm gold slab reduces the work function of gold, (ii) Rh590:PMMA increases the work function of a gold film deposited on top of the polymer, and (iii) reduces it if Rh590:PMMA is deposited on top of Au. (iv) With increase of the Rh590 concentration in PMMA, n, the work function first decreases (at n < 64 g/l), and then increases (at n > 64 g/l). (v) The work function of a Fabry–Perot cavity or an MIM waveguide is almost the same as that of single Au films of comparable thickness. The experimental results can be qualitatively explained in terms of a simple model taking into account adhesion of charged molecules to a metallic surface, and formation of a double layer of charges accelerating or decelerating electrons exiting the metal and decreasing or increasing the work function.

Assessing acoustic performance of building material: A finite element model for 3D printed multilayer micro-perforated panels with compressed earth blocks

This study deals with 3D printing multilayered micro-perforated panels (M-MPPs) coupled with buildings materials as compressed earth block for noise reduction applications. The sound absorption coefficient α is utilized as a metric to assess the sound insulation capabilities across a frequency range spanning from 10 to 3000 Hz, then evaluated and validated by numerical and experimental methods. The FEM model developed makes it possible to predict the acoustic absorption of M-MPPs by tuning the frequency range and varying optimized acoustics parameters, considering hole-hole interaction and taking into account visco-thermal effects that are present in compressed earth blocks. It is shown that the shape of perforations and material properties including the porosity rate, arrangement in the design of multilayer micro-perforated structures are identified to play a significant role in the sound performance of the entire structure. In addition, the application of MPP coupled with compressed earth blocks improve the sound absorption capacity of the composite structure. The developed FEM leads to accurate prediction of performance, efficient optimization, and cost effectiveness. Finally, the present study reveals the importance of M-MPPs combined with compressed earth blocks (CEBs) as viable noise reduction materials, particularly relevant for engineering applications and development initiatives in emerging economies.

HSC: a multi-hierarchy descriptor for loop closure detection in overhead occlusion scenes

Loop closure detection is a key technology for robotic navigation. Existing research primarily focuses on feature extraction from global scenes but often neglects local overhead occlusion scenes. In these local scenes, objects such as vehicles, trees, and buildings vary in height, creating a complex multi-layered structure with vertical occlusions. Current methods predominantly employ a single-level extraction strategy to construct descriptors, which fails to capture the characteristics of occluded objects. This limitation results in descriptors with restricted descriptive capabilities. This paper introduces a descriptor named Hierarchy Scan Context (HSC) to address this shortfall. HSC effectively extracts height feature information of objects at different levels in overhead occlusion scenes through hierarchical division, demonstrating enhanced descriptive capabilities. Additionally, a time series enhancement strategy is proposed to reduce the number of algorithmic missed detections. In the experiments, the proposed method is validated using a self-collected dataset and the public KITTI and NCLT datasets, demonstrating superior performance compared to competitive methods. Furthermore, the proposed method also achieves an average maximum F1 score of 0.92 in experiments conducted on nine selected road segments with overhead occlusion.

Numerical analysis of electrohydrodynamic printing under electric field focusing mode

As an emerging micro/nanoscale 3D printing technology, Electrohydrodynamic (EHD) printing has undergone rapid development in recent years. However, in most EHD printing processes, voltage is directly applied to both the nozzle and the substrate, resulting in the electric field being influenced by the printing height. This poses challenges for printing three-dimensional curved surface structures. This study presents a comprehensive investigation into the EHD jetting process, utilizing a novel voltage loading method that separates electrodes from both the nozzle and the substrate. Through experimental setups and numerical simulations, this research was conducted to examine the effects of printing height, voltage, and electrode diameter on jetting behavior. The results show that compared to the traditional electrode form, the new voltage loading method will increase the electric field intensity of the liquid surface before ejection by 37.1% and is more conducive to the formation of Taylor cones. It can ensure that the printing fluctuation is less than 2.4% when the printing height varies between 1.5–2.5 times the nozzle diameter, which is more favorable for printing multi-layer structures. The threshold voltage for ejection is provided in this model. When the electrode is reduced, the efficiency of electric field utilization will be further improved, but the acceleration of the jet velocity will cause an increase in droplet size. The findings highlight the method’s capability to maintain consistent droplet sizes and electric field intensities across varying conditions, thereby enhancing printing stability and efficiency. The study’s innovations provide valuable insights for advancing micro/nano 3D printing technologies, emphasizing the potential for improved EHD printing processes in practical engineering applications.

Study on the permeability and capillary pressure of spiral woven mesh for flat-plate heat pipes

Due to its excellent capillary characteristics, spiral woven mesh is widely used as the wick structure in ultra-thin flat-plate heat pipes. The performance of these heat pipes surpasses that of conventional ones using sintered powder or multi-layer mesh structures. However, precise quantitative studies on the permeability and capillary pressure characteristics of this unique porous structure are lacking. In this work, we systematically investigated its permeability and capillary pressure, as well as their relationship with the structure. Based on experimental results, we demonstrated that numerical simulation of periodic microelements and subsequent area weighting can accurately predict the permeability of actual structures. Additionally, a parametric study was conducted, yielding a unified empirical relationship between permeability and the structural parameters. In the part of capillary pressure, U-shape tube gravity method was utilized and the relationship between capillary pressure and structure was also disclosed. This study will provide reliable data and theoretical guidance for calculating the capillary limit in heat pipes using spiral woven mesh as the wick.

Estimating the Health State of Lithium-Ion Batteries Using an Adaptive Gated Sequence Network and Hierarchical Feature Construction

State of health (SOH) estimation plays a vital role in ensuring the safe and stable operation of lithium-ion battery management systems (BMSs). Data-driven methods are widely used to estimate SOH; however, existing methods often suffer from fixed or excessively high feature dimensions, impacting the model’s adjustability and applicability. This study first proposed a layered knee point strategy based on the charging voltage curve, which reduced the complexity of feature extraction. Then, a new hybrid framework called the adaptive gated sequence network (AGSN) model was proposed. This model integrated independently recurrent neural network (IndRNN) layers, active state tracking long short-term memory (AST-LSTM) layers, and adaptive gating mechanism (AGM) layers. By integrating a multi-layered structure and an adaptive gating mechanism, the SOH prediction performance was significantly improved. Finally, batteries under different operating conditions were tested using the NASA battery dataset. The results show that the AGSN model demonstrated higher accuracy and robustness in battery SOH estimation, with estimation errors consistently within 1%.

Investigation of effective parameters on Fe/Ta thin films by plasma focus device: number of shots and distance from tip anode

This experimental investigation is the first to generate a surface iron-tantalum (Fe/Ta) alloy as a sublayer-layer using a plasma focus device. Examining how ion beams from a plasma focus device alloy iron and tantalum with varying melting points is one of the key objectives of this study. Fe/Ta thin film nanostructure and surface morphology were also examined. The distance from the tip anode and the varied number of shots are the experimental variables. Although tantalum's melting point (3020 ∘C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ{\\rm C}$$\\end{document}) is generally known to be near to that of iron (2862 ∘C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ{\\rm C}$$\\end{document}), it is possible that iron vaporizes and partial alloying of iron with tantalum occurs before tantalum reaches its melting point. Fe/Ta thin film identification techniques include scanning electron microscopy, mapping of cross-section, energy dispersive X-ray spectroscopy, and X-ray diffraction pattern. Additionally, the composition of multilayer structures is examined using EDS. In conclusion, the results of the X-ray diffraction pattern showed that the number of shots had a significant impact on the residual strain degree of the thin films that were deposited. Furthermore, structures made of FeTa and Fe2Ta were produced. Additionally, photos from scanning electron microscopy and cross-section mapping verify that the sample with five shots at an 8 cm distance from the tip anode formed a uniform Fe/Ta alloy structure. The sample with five shots at a distance of 4 cm from the tip anode formed micro-island structures, as seen by scanning electron microscopy, with decreasing distance. Furthermore, depth elemental distribution revealed that the optimal depth of penetration in a homogenous material to develop alloying is best determined by number of PF shots.

Detecting low-concentration ammonia with a surface acoustic wave sensor using a silver nanoparticles–graphene–polypyrrole hybrid nanocomposite film

In this study, a surface acoustic wave (SAW) resonator coated with graphene/polypyrrole hybrid nanocomposite films decorated with silver nanoparticles (AgNPs-G/PPy) is proposed for detecting ammonia (NH3) in parts-per-billion concentrations. The AgNPs-G/PPy hybrid nanocomposite film was synthesized via in situ chemical oxidative polymerization. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction were used to characterize the AgNPs-G/PPy hybrid nanocomposite film, confirming its successful synthesis and identifying a wrinkled multilayered structure. The AgNPs-G/PPy hybrid nanocomposite film was spin-coated onto the surface of a stress-compensated temperature-cut quartz SAW resonator having an operating frequency of 98.5 MHz to create an NH3 gas sensor. NH3 adsorption by the AgNPs-G/PPy hybrid nanocomposite film modulated the acoustic wave velocity, and the corresponding frequency shift served as a sensing signal. The synergistic interaction between the three constituent materials (AgNPs, graphene, and polypyrrole) enhanced the sensitivity, selectivity, and response speed of the sensor for NH3 detection. At room temperature, the proposed sensor exhibited a positive frequency shift of 568 Hz when exposed to 50 ppb of NH3 gas and a rapid response time of less than 60 s. In addition, the SAW sensor exhibited excellent selectivity.

Asymptotic multilayer pooled transformer based strategy for medical assistance in developing countries

With the continuous progress of medical imaging technology, pathology images have become an important basis for doctors to judge the condition. However, pathology images have problems such as large numbers, large sizes, and complex backgrounds, which make the task of manual recognition exceptionally difficult. The use of computer-aided diagnosis technology can improve the diagnostic accuracy of medical image recognition. Transformer model-based methods have made great progress in the field of medical image recognition, but the self-attention mechanism in them has high computational complexity. Although single-layer pooling can reduce the computational cost, the strategy is prone to feature loss, and too many self-attention operations can exacerbate the distraction problem. Based on this, this study proposes an asymptotic multilayer pooling transformer-based pathology image assistance strategy in medical decision-making systems. First, we pre-process the pathology images with denoising and enhancement to accurately capture the detailed features of the lesion region. Then the asymptotic multilayer pooling transformer pyramid structure (PMPSNet) is used to identify cell nuclei. In the self-focused module, a multilayer pooling operation is employed to simplify the sequence and efficiently capture contextual features. In addition, the strategy utilizes a pyramid encoder to obtain multi-scale feature maps and a novel multilayer perceptual structure to limit the attention interference problem. The results show that our proposed PMPSNet-L model achieves a DSC value of 0.822, which is about 1.4 % better than the second-ranked model, and the IoU value reaches up to 0.702. In addition, our PMPSNet-S maintains a relatively lightweight parameter size of about 14.49 million, which is considerably lower than the existing segmentation models. Our proposed method not only achieves higher segmentation accuracy but also has fewer model parameters and lower computational complexity.

Abstract Mo032: Biofabrication of Small Vascular Graft using Human Amniotic Membrane

Vascular diseases encompass a spectrum of pathological conditions affecting blood vessels, including cerebrovascular disease, coronary heart disease, aneurysms, deep vein thrombosis, and peripheral arterial disease. In severe cases, surgical interventions such as bypass grafting or vascular replacement surgeries are necessary to restore blood flow by bypassing obstructed vessels with functional vascular substitutes. Autologous blood vessels harvested from patients are considered the gold standard for vascular surgeries. However, their availability is limited in patients with pre-existing chronic diseases or previous vessel harvest, and the associated morbidities of vessel harvesting and subsequent surgeries further restrict their therapeutic applicability. Synthetic grafts, including polytetrafluoroethylene (e-PTFE), polyethylene terephthalate (PET), and polyurethane (PU), have obtained FDA approval for clinical application and have shown satisfactory outcomes in large vessel surgeries (internal diameter &gt; 6mm). However, clinical trials targeting medium (6-10 mm) to small (&lt; 6mm) vessels often yield unsatisfactory results. This study aims to develop a small vascular graft using human amniotic membrane (HAM) that meets the structural, mechanical, and biological requirements for human vascular reconstructive surgeries. Fresh HAMs were decellularized with 1% Triton X-100 and 0.1% sodium dodecyl sulfate to prepare decellularized HAM (DAM). The DAM was trimmed into a rectangular shape and rolled around a catheter to prepare a tubular-shaped DAM vascular graft. After rolling, the DAM grafts were crosslinked with 1% genipin for 24 hours followed by thorough water washing. The final DAM vascular graft exhibited a multi-layered wall structure and comparable dimensions and mechanical properties to native arteries. The DAM vascular graft was further evaluated in vivo by replacing part of the rat abdominal aorta and part of the carotid artery in pigs. Both small and large animal studies demonstrated vascular patency with no neointimal hyperplasia (NIH), suggesting that the DAM graft holds significant promise as a small tissue-engineered vascular graft for future vascular reconstruction surgeries.

Topologically guided exfoliation of 3D metal-organic frameworks into nanosheets

Herein a general concept for screening 3D metal-organic frameworks (MOFs) for 2D nanosheets design is presented. Active coordination centers and terminal ligands of 3D-to-2D MOF nanosheets can result in self-assembly of multilayer structures. In comparison to 2D MOFs, 3D frameworks can provide nanosheets with better adhesion, strength, adsorptive capacity and catalytic activity. They are also promising in semiconductors, sensorics, and drug delivery systems. However, less than a dozen of 3D-to-2D MOF nanosheets have been produced to date. Therefore, we applied topological tools of ToposPro and Cambridge Structural Database for screening 3D MOFs as sources of new 2D nanosheets. Cluster representation uncovered the potential existence of 2D nanosheets as subnets of 3D networks in 3032 structures. Furthermore, parameters of building units, net topologies, and accessible channels were analyzed. The concept was proved by synthesis and successful exfoliation of new compound [Zn4(THIP)(HCO2)3(H2O)4]∙DMF (1), which was assembled from 4,5,6-trihydroxyisophtalic acid (H5THIP) as intralayer linker, formate anions as both intralayer linker and interlayer pillar, and Zn(II) as coordination center. In the compound, H5THIP shows complete deprotonation that is unique for hydroxyisophthalate ligands. The crystalline phase of the compound was studied by SCXRD, PXRD, FTIR, and TGA measurements. Nanosheets of height 0.1–90 nm and lateral sizes above 400 nm were produced by sonication of crystals in ethanol. The exfoliation was proved by SEM with EDS, PXRD, AFM, TEM, and BET surface measurements.

Multi-frame temporal dense nested attention method for detecting GEO objects

The geostationary orbit is a special and important spatial orbital resource. However, space resident objects in this orbit pose potential threats to space security, characterized as dim and small targets in imaging features. To solve the problem of detecting dim and small targets in geostationary orbit, we propose a multi-frame temporal dense nested attention method, which consists of a uniform linear motion constraint module and a dense nested attention module. The dense nested attention module adopts a multi-layer U-shaped structure and channel spatial attention mechanism, which can preserve the deep features of small targets, extract and fuse features from different scales of feature maps, and finally obtain the preliminary detection results of single-frame images. The uniform linear motion constraint module uses the prior information of the target motion in the image sequence, removes false positives and supplements false negatives, and improves the detection performance. Experiments were conducted on the SpotGEO dataset publicly released by the European Space Agency. The results of our experiments indicate that our method outperforms the state-of-the-art approach, showing a 12.83% reduction in Mean Squared Error compared to the current leading method. Our method, characterized by its minimal parameter requirement and independence from extensive dataset pre-training, is ideally suited for integration into small satellite devices, enabling efficient monitoring and mitigation of resident space objects.

Study on the adsorption properties of lysozyme by cellulose microspheres modified with reactive red 120

Microspheres of cellulose acetate, characterized by a multi-layered, uniform, and continuous porous structure, were synthesized through the process of emulsion evaporation. Subsequent deacetylation facilitated the modification of the cellulose microspheres’ surface, which was functionalized with Reactive Red 120, serving as an affinity dye ligand. This modification yielded a cationic adsorbent. The adsorptive behavior of lysozyme from aqueous solutions, with lysozyme designated as the target protein, was examined in relation to the effects of pH and ionic strength. The adsorptive capacity of the cellulose microspheres, modified with Reactive Red 120, for lysozyme was determined to be 106.57 mg g−1, exhibiting rapid equilibration within 40 min. The adsorption kinetics and thermodynamics were accurately described by the pseudo-second-order kinetic model and the Langmuir model, respectively, with correlation coefficients (R2) of 0.98 and 0.97. Furthermore, dynamic adsorption experiments revealed an enhanced adsorption capacity of 36.5 mg g−1, significantly surpassing that of the unmodified microspheres. The cellulose microspheres, derived from cellulose acetate and modified accordingly, are environmentally benign and sustainable, thereby holding significant promise for various biological applications.

Ultra-Sensitive and Selective Surface Plasmon Resonance using Ag Metal, Carbon Nanotube, and Selenium Based Biosensors for the Detection of Ascorbic Acid

In this work, we present a novel surface plasmon resonance (SPR) sensor for ascorbic acid detection based on a borosilicate crown (BK7) prism coated with a multilayer structure made of ferric oxide (Fe2O3), silver (Ag), and carbon nanotube (CNT). The SPR sensor improves sensitivity and selectivity for ascorbic acid detection by taking advantage of the special optical characteristics of the multilayer construction. The CNT layer offers increased surface area and biocompatibility, and the Ag layer acts as a plasmonic material to promote surface plasmons. The performance of the sensor is improved by the addition of selenium (Se) and Fe2O3 layers, which provide further capabilities like photoconductivity and magnetic manipulation, respectively. Numerical analysis at the operating wavelength of 633 nm is conducted using the transfer matrix approach. For the proposed SPR sensor at room temperature, the performance characteristics, including sensitivity (274.37 degree (°)/RIU), figure of merit (40.60 RIU−1), and detection accuracy (0.189°−1), are computed. The proposed SPR sensor could be very useful in to detect ascorbic acid in the visible range.