Search Results (232)

Two-dimensional (2D) material-based resistive random-access memory (RRAM) has emerged as a promising solution for neuromorphic computing and computing-in-memory architectures. Compared to conventional metal-oxide-based RRAM, the novel 2D material-based RRAM devices demonstrate lower power consumption, higher integration density, and reduced performance variability, benefiting from their atomic-scale thickness and ultra-flat surfaces. Remarkably, 2D layered metal oxides retain these advantages while preserving the merits of traditional metal oxides, including their low cost and high environmental stability. Through a multi-step dry transfer process, we fabricated a Pd-MoO₃-Ag RRAM device featuring 2D α-MoO₃ as the resistive switching layer, with Pd and Ag serving as inert and active electrodes, respectively. Resistive switching tests revealed an excellent operational stability, low write voltage (~0.5 V), high switching ratio (>10⁶), and multi-bit storage capability (≥3 bits). Nevertheless, the device exhibited a limited retention time (~2000 s). To overcome this limitation, we developed a Gr-MoO₃-Ag heterostructure by substituting the Pd electrode with graphene (Gr). This modification achieved a fivefold improvement in the retention time (>10⁴ s). These findings demonstrate that by controlling the type and thickness of 2D materials and resistive switching layers, RRAM devices with both high On/Off ratios and long-term data retention may be developed. Full article

Geological hazards pose significant threats to ecological stability, human lives, and infrastructure, necessitating precise and robust risk assessment methodologies. This study evaluates geological hazard risks in Dawukou District, Shizuishan City, Ningxia Hui Autonomous Region, using the information value (IV) model. The study systematically identifies susceptibility, hazard, and vulnerability factors influencing geological disaster risks by integrating diverse datasets encompassing geological conditions, meteorological parameters, and anthropogenic activities. The key findings reveal that hilly landforms, slope gradients, and vegetation indices are the dominant contributors to hazard development. Additional factors, including lithology, fault proximity, and precipitation, were also found to play critical roles. The results categorize the district into four risk zones: high-risk areas (1.55% of the total area), moderate-risk areas (10.16%), Low-risk areas (23.32%), and very-low-risk areas (64.97%). These zones exhibit a strong spatial correlation with geomorphic features, tectonic activity, and human engineering interventions, such as mining and infrastructure development. High-risk zones are concentrated near mining regions and fault lines with steep slopes, while low-risk zones are predominantly in flat plains and urban centers. The reliability of the risk assessment was validated through cross-referenced geological hazard occurrence data and Receiver Operating Characteristic (ROC) curve analysis, achieving a high predictive accuracy (AUC = 0.88). The study provides actionable insights for disaster prevention, mitigation strategies, and urban planning, offering a scientific basis for resource allocation and sustainable development. The methodology and findings serve as a replicable framework for geological hazard risk assessments in similar regions facing diverse environmental and anthropogenic challenges. Full article

E. coli attaches to, and forms biofilms on various surfaces, including latex and polystyrene, contributing to nosocomial spread. E. coli responds to both exogenous and endogenous insulin, which induces behavioral changes. Human insulin, a quorum signal surrogate for microbial insulin, may affect the ability of E. coli to interact with latex and polystyrene in the presence of various sugars. E. coli ATCC 25923 was grown in peptone (1%) yeast nitrogen base broth to either the logarithmic or stationary growth phase. Adherence to latex was determined using 6 × 6 mm latex squares placed in a suspension of washed cells (10³ CFU/mL; 30 min; 37 °C) in buffer containing insulin at 2, 20, and 200 µU/mL (Humulin^® R; Lilly) with and without mannose, galactose, fructose, sorbose, arabinose, xylose, lactose, maltose, melibiose, glucose-6-phosphate, glucose-1-phosphate, and glucosamine at concentrations reported to affect behavioral response. Attachment levels to latex were determined by the press plate method. Biofilm levels were measured in a similar fashion but with overnight cultures in flat bottom uncoated polystyrene plates. Controls were media, insulin, sugar, or buffer alone. Glucose served as the positive control. Overall, the stationary phase cells’ adherence to latex was greater, regardless of the test condition, than was measured for the logarithmic phase cells. The effect of insulin on adherence to latex was insulin and sugar concentration dependent. The addition of insulin (200 µU/mL) resulted in a significantly (p < 0.05) increased adherence to latex and biofilm formation on polystyrene compared with sugar alone for 12 of the 13 sugars tested with stationary phase bacteria and 10 of the 13 sugars tested with logarithmic phase bacteria. Adherence in response to sorbose was the only sugar tested that was unaffected by insulin. These findings show that insulin enhances E. coli’s association with materials in common usage in medical environments in a nutrition-dependent manner. Full article

As a crucial characteristic waterfowl breed, the egg-laying performance of Lion-Headed Geese serves as a core indicator for precision breeding. Under large-scale flat rearing and selection practices, high phenotypic similarity among individuals within the same pedigree coupled with traditional manual observation and existing automation systems relying on fixed nesting boxes or RFID tags has posed challenges in achieving accurate goose–egg matching in dynamic environments, leading to inefficient individual selection. To address this, this study proposes YOLO-Goose, an improved YOLOv8s-based method, which designs five high-contrast neck rings (DoubleBar, Circle, Dot, Fence, Cylindrical) as individual identifiers. The method constructs a lightweight model with a small-object detection layer, integrates the GhostNet backbone to reduce parameter count by 67.2%, and employs the GIoU loss function to optimize neck ring localization accuracy. Experimental results show that the model achieves an F1 score of 93.8% and mAP50 of 96.4% on the self-built dataset, representing increases of 10.1% and 5% compared to the original YOLOv8s, with a 27.1% reduction in computational load. The dynamic matching algorithm, incorporating spatiotemporal trajectories and egg positional data, achieves a 95% matching rate, a 94.7% matching accuracy, and a 5.3% mismatching rate. Through lightweight deployment using TensorRT, the inference speed is enhanced by 1.4 times compared to PyTorch-1.12.1, with detection results uploaded to a cloud database in real time. This solution overcomes the technical bottleneck of individual selection in flat rearing environments, providing an innovative computer-vision-based approach for precision breeding of pedigree Lion-Headed Geese and offering significant engineering value for advancing intelligent waterfowl breeding. Full article

The iron and steel industry is a major emitter of carbon. In the context of China’s dual-carbon goals, hydrogen-based reduction ironmaking technology has garnered unprecedented attention. It is considered a crucial approach to reducing carbon dioxide emissions in the steel sector and facilitating the realization of carbon neutrality. This work conducted isothermal thermogravimetric analysis on limonite ore in a N₂/H₂ atmosphere. The influences of reduction temperature, particle size, and hydrogen partial pressure on the hydrogen reduction reaction process of limonite were investigated. Based on the principles of isothermal thermal analysis kinetics and the unreacted core model for flat-plate particles, the mechanism function and kinetic parameters for the reduction of limonite particles were determined. The research results show that the hydrogen reduction process of limonite ore is influenced by multiple factors, including temperature, hydrogen partial pressure, and particle size. Increasing the reduction temperature and hydrogen partial pressure can significantly speed up the reduction reaction rate and enhance the degree of reduction. The kinetic parameters for the hydrogen reduction of limonite particles were obtained as follows: the reaction activation energy was 44.738 kJ·mol⁻¹, the pre-exponential factor was 31.438 m·s⁻¹, and the rate constant for the hydrogen reduction of limonite was $k=31.438\times e^{-{\displaystyle \frac{44.738\times 1000}{RT}}}\mathrm{m}\cdot {\mathrm{s}}^{-1}$. In addition, contour maps were plotted to predict the reaction time and reaction temperature required for a complete reduction of limonite particles of different sizes to iron (Fe) particles under varying hydrogen partial pressures. The research findings can serve as a scientific basis for optimizing hydrogen-based reduction ironmaking technology in the iron and steel industry and achieving carbon neutrality goals. Full article

The widespread deployment of electric vehicles (EVs) has introduced substantial challenges to electricity pricing, grid stability, and renewable energy integration. This paper presents the first real-time quantum-enhanced electricity pricing framework for large-scale EV charging networks, marking a significant departure from existing approaches based on mixed-integer programming (MILP) and deep reinforcement learning (DRL). The proposed framework incorporates renewable intermittency, demand elasticity, and infrastructure constraints within a high-dimensional optimization model. The objective is to dynamically determine spatiotemporal electricity prices that reduce system peak load, improve renewable utilization, and minimize user charging costs. A rigorous mathematical formulation is developed, integrating over 40 system-level constraints, including power balance, transmission limits, renewable curtailment, carbon targets, voltage regulation, demand-side flexibility, social participation, and cyber-resilience. Real-time electricity prices are treated as dynamic decision variables influenced by station utilization, elasticity response curves, and the marginal cost of renewable and grid electricity. The model is solved across 96 time intervals using a quantum-classical hybrid method, with benchmark comparisons against MILP and DRL baselines. A comprehensive case study is conducted on a 500-station EV network serving 10,000 vehicles, coupled with a modified IEEE 118-bus grid and 800 MW of variable renewable energy. Historical charging data with ±12% stochastic demand variation and real-world solar/wind profiles are used to simulate realistic conditions. Results show that the proposed framework achieves a 23.4% average peak load reduction per station, a 17.9% gain in renewable utilization, and up to 30% user cost savings compared to flat-rate pricing. Network congestion is mitigated at over 90% of high-traffic stations. Pricing trajectories align low-price windows with high-renewable periods and off-peak hours, enabling synchronized load shifting and enhanced flexibility. Visual analytics using 3D surface plots and disaggregated bar charts confirm structured demand-price interactions and smooth, stable price evolution. These findings validate the potential of quantum-enhanced optimization for scalable, clean, and adaptive EV charging coordination in renewable-rich grid environments. Full article

Smart construction technology integrates artificial intelligence, Internet of Things, UAVs, and building information modeling to improve productivity and quality in construction. In road embankment earthworks, ground compaction quality is critical for structural stability and maintenance. This study proposes a methodology combining UAV photogrammetry with intelligent compaction quality management systems to evaluate surface flatness and compaction homogeneity in real-time. High-resolution UAV images were used to generate digital elevation models, from which surface roughness was extracted using terrain element analysis and fast Fourier transform. Local terrain changes were interpreted through contour gradient, outline gradient, and tangential gradient curvature analysis. Field tests were conducted at a pilot site using a vibratory roller, followed by four compaction quality assessments: plate load test, dynamic cone penetration test, light falling weight deflectometer, and compaction meter value. UAV-based flatness analysis revealed that, when surface flatness met the standard, a strong correlation was observed, with results from conventional field tests and intelligent compaction data. The proposed method effectively identified poorly compacted zones and spatial inhomogeneity without interrupting construction. These findings demonstrate that UAV-based terrain analysis can serve as a nondestructive real-time monitoring tool and contribute to automated quality control in smart construction environments. Full article

The performance of electrochemical (bio)sensors is fundamentally determined by the precise engineering of interfacial layers that govern (bio)analyte–surface interactions. However, elucidating structure–function relationships remains challenging due to the complex architecture of modern sensors and the irregular nanoscale morphology of many high-performance materials. In this study, we present a strategy for designing custom functional interfaces as well-defined platforms for probing interfacial processes. Focusing on epinephrine (EP) detection as an important representative of catecholamines, we compare the interfacial behavior of two carboxy-functionalized electrodes—grafted with either para-aminobenzoic acid (PAB) or 3,4,5-tricarboxybenzenediazonium (ATA)—against atomically flat highly oriented pyrolytic graphite (HOPG) as a control. While both modifiers introduce carboxyl groups, PAB forms disordered multilayers that inhibit surface responsiveness, whereas ATA yields an ultrathin monolayer with accessible COOH groups. Electrochemical analysis reveals that ATA-HOPG significantly enhances EP detection at sub-micromolar levels, facilitated by electrostatic interactions between surface-bound COO⁻ and protonated EP and its redox products. These results demonstrate that nanoscale control of diazonium grafting is crucial for optimizing bioanalyte recognition. More broadly, this work highlights how molecular-level surface engineering on high-quality carbon substrates can serve as a test-bed platform for the rational design of advanced electrochemical sensing interfaces. Full article

A very fundamental property of both weakly and strongly interacting materials is the nature of their magnetic response. In this work, we detail the growth of crystals of the quasicrystal approximant Fe₄Al₁₃ with an Al flux solvent method. We characterize our samples using electrical transport and heat capacity, yielding results consistent with a simple non-magnetic metal. However, magnetization measurements portray an extremely unusual response for a dilute paramagnet and do not exhibit the characteristic Curie behavior expected for a weakly interacting material at high temperature. Electronic structure calculations confirm metallic behavior but also indicate that each isolated band near the Fermi energy hosts non-trivial topologies, including strong, weak, and nodal components, with resultant topological surface states distinguishable from bulk states on the (001) surface. With half-filled flat bands apparent in the calculation, but an absence of long-range magnetic order, the unusual quasi-paramagnetic response suggests the dilute paramagnetic behavior in this quasicrystal approximant is surprising and may serve as a test of the fundamental assumptions that are taken for granted for the magnetic response of weakly interacting systems. Full article

Cylindrical joints serve as critical pathways for heat flow in various applications, including heat pipes, electronic devices, and fin-tube heat exchangers. Despite their significance, research has predominantly focused on flat joints, with limited investigation into cylindrical joints, especially on how cylindrical thermal contact conductance (TCC) changes in response to temperature and heat flux, a feature distinctive to cylindrical joints. This study provides a comprehensive theoretical and numerical investigation of cylindrical TCC behavior across various material combinations and heat flux directions. We identified three response modes for outward heat flux and six for inward heat flux, classified by the relative thermal expansion coefficients and heat flux direction. Notably, under inward heat flux, we discovered a previously unreported phenomenon: two possible contact states occurring at identical interfacial temperature, heat flux, and material conditions, with TCC values differing by more than an order of magnitude. The study covers a wide range of conditions (temperatures from 293 K to 1400 K and heat fluxes from 10⁴ to 10⁶ W/m²), confirming that the identified response patterns are broadly applicable and governed by general principles rather than specific material properties or geometric parameters. These findings provide new insights into cylindrical joint behavior and offer valuable guidelines for optimizing the design and performance of thermal systems involving cylindrical interfaces. Full article

The visual system has served as an expeditious entry point for discerning the mechanism of action of many brain systems, spearheading multiple fields of neuroscience in the process. It has additionally launched the careers of countless scientists, as we have crafted new means to understand neuronal structures and their functions, leading to advances in many areas of the sciences. Indeed, one can readily mark the onset of the scientific examination of the visual system with the 1851 invention of the ophthalmoscope by Hermann von Helmholtz, and the trichromatic theory of color vision in 1802. The Young–Helmholtz understanding the red–green–blue nature of color vision became the foundation to understanding sensory system function that visual artists and also contemporary flat panel displays rely on. It is fascinating to realize that the paintings of Georges Seurat and an iPhone display share a commonality of this application of the trichromatic theory. While it was not until 1956 that the existence of cells responsive to three different ranges of wavelengths was proven with the work of Gunnar Svaetichin, this proof in many ways marked the advancement of tools to visualize at a microscopic level, a full century after the Young–Helmholtz theory was developed. Just a decade later, in 1966, the person widely considered as the founder of modern neuroscience, Stephen Kuffler, founded the Harvard neurobiology department. It was from Kuffler’s work with his post-doctoral students that many new fields of study were created and from whom many of the neuroscience programs across the US were founded. In terms of the visual system, Kuffler and his team were key in detailing areas of retinal neuroanatomy, neurochemistry, neurophysiology, and developmental neurobiology. This paper traces areas in visual system research that provide our understanding of the disparate areas of brain sciences. As such, there are six categories that are evaluated, each of which spawned work in multiple areas that have become mainstays in neuroscience. These range from fields that were dominant a half century ago to ones that have their origins in this decade. The commonality is that all of these owe their origin to Helmholtz and Kuffler, polymaths of the nineteenth and twentieth centuries. We will examine the impact of vision research across the following fields of neuroscience: sensory system function, neuroanatomy, neurochemistry, neurophysiology, developmental neurobiology, and neurological health and disease. Full article

Marine antifouling coatings that rely on the release of antifouling agents are the most prevalent and effective strategy for combating fouling. However, the environmental concerns arising from the widespread discharge of these agents into marine ecosystems cannot be overlooked. An innovative and promising alternative involves incorporating antimicrobial groups into polymers to create coatings endowed with intrinsic antimicrobial properties. In this study, we reported an urushiol-based benzoxazine (URB) monomer, synthesized from natural urushiol and antibacterial rosin amine. The URB monomer was subsequently polymerized through thermal curing ring-opening polymerization, resulting in the formation of a urushiol-based benzoxazine polymer (URHP) coating with inherent antimicrobial properties. The surface of the URHP coating is smooth, flat, and non-permeable. Contact angle and surface energy measurements confirm that the URHP coating is hydrophobic with low surface energy. In the absence of antimicrobial agent release, the intrinsic properties of the URHP coating can effectively kill or repel fouling organisms. Furthermore, with bare glass slides serving as the control sample, the coating demonstrates outstanding anti-adhesion capabilities against four types of bacteria (E. coli, S. aureus, V. alginolyticus, and Bacillus sp.), and three marine microalgae (N. closterium, P. tricornutum, and D. zhan-jiangensis), proving its efficacy in preventing fouling organisms from settling and adhering to the surface. Thus, the combined antibacterial and anti-adhesion properties endow the URHP coating with superior antifouling performance. This non-release antifouling coating represents a green and environmentally sustainable strategy for antifouling. Full article

To reduce the power consumption of rotary tillage and enhance the operational quality of rotary tillage, a rotary blade that imitates the surface of a pufferfish was designed through reverse engineering. The bump structure on the pufferfish surface was employed to decrease the power consumption when the blades till the soil. The performance of the bionic blade was investigated. A single-factor soil bin test was conducted, with the forward speed of the rotary tiller and the rotation speed of the blade shaft serving as the test factors, and the power consumption of the rotary tiller and the ground surface flatness as the evaluation indexes. The test results revealed that the power consumption of the rotary tiller initially decreases, then increases, and finally decreases with the increase in the forward speed of the rotary tiller. It is positively correlated with the rotation speed of the blade shaft. The ground surface flatness is positively correlated with the forward speed of the rotary tiller but negatively correlated with the rotation speed of the blade shaft. Compared with the rotary tiller with standard IT225 blades, the rotary tiller with bionic blades achieves a 9.4% reduction in power consumption and a 6.5% improvement in ground surface flatness. This study has demonstrated that the bump structure of the pufferfish surface can effectively reduce the power consumption of the blades and enhance ground surface quality, thus offering novel insights for the development of energy-saving tillage tools. Full article

Renewable energy technologies have become an increasingly important component of the global energy supply. In recent years, photovoltaic and wind energy have been the fastest-growing renewable sources. Although oceans present harsh environments, their estimated energy generation potential is among the highest. Ocean-based solutions are gaining significant momentum, driven by the advancement of offshore wind, floating solar, tidal, and wave energy, among others. The integration of various marine energy sources with green hydrogen production can facilitate the exploitation and transportation of renewable energy. This paper presents a mathematics-driven analysis for the simulation of a technical model designed as a generic framework applicable to any location worldwide and developed to analyze the integration of solar energy generation and green hydrogen production. It evaluates the impact of key factors such as solar irradiance, atmospheric conditions, water surface flatness, as well as the parameters of photovoltaic panels, electrolyzers, and adiabatic compressors, on both energy generation and hydrogen production capacity. The proposed mathematics-based framework serves as an innovative tool for conducting multivariable parametric analyses, selecting optimal design configurations based on specific solar energy and/or hydrogen production requirements, and performing a range of additional assessments including, but not limited to, risk evaluations, cause–effect analyses, and/or degradation studies. Enhancing the efficiency of solar energy generation and hydrogen production processes can reduce the required photovoltaic surface area, thereby simplifying structural and anchoring requirements and lowering associated costs. Simpler, more reliable, and cost-effective designs will foster the expansion of floating solar energy and green hydrogen production in marine environments. Full article

A five-bed, seven-step vacuum pressure swing adsorption (VPSA) system was computationally modeled to assess carbon monoxide (CO) separation from CO/N₂ mixed gas (30/70, v/v). Two adsorbents with distinct isotherm characteristics (steep-slope CuCl/NaY and flat-slope CuCl/AC) were comparatively evaluated for their process performance, focusing on CO purity, recovery, productivity, and energy consumption. The simulation results demonstrate that under industrial-grade specifications requiring both adsorbents to achieve CO purity > 97% and recovery > 83%, CuCl/AC achieves a 3.9-fold higher productivity (27.238 vs. 7.016 mol kg⁻¹ h⁻¹) than CuCl/NaY while maintaining a comparable energy consumption. This performance disparity stems from CuCl/AC’s enhanced bed layer CO desorption amount during a cyclic VPSA operation, which enhances feed gas throughput per unit adsorbent mass. This study demonstrates that CuCl/AC, with its flat-slope adsorption isotherm and high desorption amount, can serve as a promising adsorbent for achieving high-purity CO with a significantly enhanced productivity via the VPSA process. Full article