Search Results (51)

Implementing effective water control measures in horizontal wells is essential for sustaining stable production in offshore oilfields. However, due to complex reservoir geological characteristics and diverse water control technologies, significant variability exists in the effectiveness of such measures, posing challenges for strategy selection. To address this gap, this study establishes a comprehensive and standardized multi-dimensional indicator system for describing treated wells, integrating geological, operational, and production parameters—an aspect seldom systematized in previous research. A major innovation of this work lies in developing a hybrid correlation evaluation framework that combines Pearson, Spearman, and canonical correlation analyses, enabling a more robust quantification of the relationships between influencing factors and water control effectiveness. This framework not only identifies the dominant indicators but also mitigates the limitations of single-method correlation analysis. Building upon these insights, the study proposes a machine learning-driven prediction system using Random Forest and Gradient Boosting algorithms, achieving classification accuracy exceeding 80% and effective regression prediction of measure duration. This represents a practical advancement over traditional empirical or single-feature decision approaches. The results reveal that overall field water cut percentage, 30-day pre-treatment water cut percentage, and daily liquid production are the key indicators governing treatment performance. Furthermore, water control measures in edge water reservoirs show significantly better performance than those in bottom water reservoirs. The developed prediction model provides a generalizable, data-driven decision-support tool, offering significant value for optimizing water control technologies in offshore horizontal wells. Full article

In this review, we focus on group IV one-dimensional devices for quantum technology. We outline the foundational principles of quantum computing before delving into materials, architectures and fabrication routes, separately, by comparing the bottom-up and top-down approaches. We demonstrate that due to easily tunable composition and crystal/interface quality and relatively less demanding fabrications, the study of grown nanowires such as core–shell Ge-Si and Ge hut wires has created a very fruitful field for studying unique and foundational quantum phenomena. We discuss in detail how these advancements have set the foundations and furthered realization of SETs and qubit devices with their specific operational characteristics. On the other hand, top-down processed devices, mainly as Si fin/nanowire field-effect transistor (FET) architectures, showed their potential for scaling up the number of qubits while providing ways for very large-scale integration (VLSI) and co-integration with conventional CMOS. In all cases we compare the fin/nanowire qubit architectures to other closely related approaches such as planar (2D) or III–V qubit platforms, aiming to highlight the cutting-edge benefits of using group IV one-dimensional morphologies for quantum computing. Another aim is to provide an informative pedagogical perspective on common fabrication challenges and links between common FET device processing and qubit device architectures. Full article

Nanophotonics, the study of light–matter interactions at the nanometer scale, has emerged as a transformative field that bridges photonics and nanotechnology. Using engineered nanomaterials—including plasmonic metals, high-index dielectrics, two-dimensional (2D) materials, and hybrid systems—nanophotonics enables light manipulation beyond the diffraction limit, unlocking novel applications in sensing, imaging, and quantum technologies. This review provides a comprehensive overview of recent advances (post-2020) in nanophotonic materials, fabrication methods, and their cutting-edge applications. We first discuss the fundamental principles governing nanophotonic phenomena, such as localized surface plasmon resonances (LSPRs), Mie resonances, and exciton–polariton coupling, highlighting their roles in enhancing light–matter interactions. Next, we examine state-of-the-art fabrication techniques, including top-down (e.g., electron beam lithography and nanoimprinting) and bottom-up (e.g., chemical vapor deposition and colloidal synthesis) approaches, as well as hybrid strategies that combine scalability with nanoscale precision. We then explore emerging applications across diverse domains: quantum photonics (single-photon sources, entangled light generation), biosensing (ultrasensitive detection of viruses and biomarkers), nonlinear optics (high-harmonic generation and wave mixing), and integrated photonic circuits. Special attention is given to active and tunable nanophotonic systems, such as reconfigurable metasurfaces and hybrid graphene–dielectric devices. Despite rapid progress, challenges remain, including optical losses, thermal management, and scalable integration. We conclude by outlining future directions, such as machine learning-assisted design, programmable photonics, and quantum-enhanced sensing, and offering insights into the next generation of nanophotonic technologies. This review serves as a timely resource for researchers in photonics, materials science, and nanotechnology. Full article

High-strength steel has high strength and low thermal conductivity, and its thin-walled parts are very susceptible to residual stress and deformation caused by cutting heat during the drilling process, which affects the machining accuracy and quality. High-strength steel thin-walled components are widely used in aerospace and other high-end sectors; however, systematic investigations into their temperature fields during drilling remain scarce, particularly regarding the evolution characteristics of the temperature field in thin-wall drilling and the quantitative relationship between drilling parameters and these temperature variations. This paper takes the thin-walled parts of AF1410 high-strength steel as the research object, designs a special fixture, and applies infrared thermography to measure the bottom surface temperature in the thin-walled drilling process in real time; this is carried out in order to study the characteristics of the temperature field during the thin-walled drilling process of high-strength steel, as well as the influence of the drilling dosage on the temperature field of the bottom surface. The experimental findings are as follows: in the process of thin-wall drilling of high-strength steel, the temperature field of the bottom surface of the workpiece shows an obvious temperature gradient distribution; before the formation of the drill cap, the highest temperature of the bottom surface of the workpiece is distributed in the central circular area corresponding to the extrusion of the transverse edge during the drilling process, and the highest temperature of the bottom surface can be approximated as the temperature of the extrusion friction zone between the top edge of the drill and the workpiece when the top edge of the drill bit drills to a position close to the bottom surface of the workpiece and increases with the increase in the drilling speed and the feed volume; during the process of drilling, the highest temperature of the bottom surface of the workpiece is approximated as the temperature of the top edge of the drill bit and the workpiece. The maximum temperature of the bottom surface of the workpiece in the drilling process increases nearly linearly with the drilling of the drill, and the slope of the maximum temperature increases nearly linearly with the increase in the drilling speed and feed, in which the influence of the feed on the slope of the maximum temperature increases is larger than that of the drilling speed. Full article

Zirconia ceramics are promising materials for restoration and are widely used in the field of artificial teeth. However, wear resistance affects the longevity of artificial teeth. In this study, peacock tail feather micro-textures and groove micro-textures are prepared on the surfaces of zirconia ceramics via the laser ablation technique to improve their tribological properties. The effects of micro-textures on the surface wettability and tribological properties of zirconia ceramics are studied. The micro-textures improve the surface wettability and tribological properties of zirconia ceramics. The average coefficient of friction of peacock tail feather micro-textured samples decreases by 53% compared to that of the samples without micro-textures. Different operating conditions affect the friction properties of zirconia ceramics. The samples have the best friction performance when the rotational speed, load, and acid/alkaline environment are 200 r/min, 15 N, and weakly alkaline, respectively. Furthermore, the mechanism by which surface micro-textures reduce frictional wear is as follows: the textured grooves store debris, and the bottom edge of the textured groove acts as a cutting tool to cut debris, preventing debris from scratching the surface. The micro-textures store lubricant and form a liquid film on the ceramic surface to reduce wear. Full article

The prediction of structural fractures in concealed coal-bearing strata has always been a complex problem. The purpose of this study was to clarify the tectonic evolution of the study area, i.e., the Tucheng syncline, since the coal-forming period and to predict the development of structural fractures. The tectonic evolution of the study area was divided into three stages using regional tectonic analysis. The paleotectonic stress field of the study area was reconstructed through the field investigation, statistics, and analysis of joints. Based on the tectonic deformation analysis, numerical simulation was used to reveal the stress field characteristics of different tectonic deformation stages, and combined with the Mohr–Coulomb criterion, the degree of structural fracture development in the target layers (No.17^# coal seam) of the study area was predicted. This study concludes the following: (1) The study area underwent two tectonic deformations during the Yanshanian period, transitioning from an ellipsoidal columnar shape to a semi-ellipsoidal and stereotyped form, forming a superimposed short-axis syncline, and then tilting southeastward as a whole, and was locally cut by faults during the Himalayan period. (2) The distribution characteristics of the stress field in different tectonic stages vary. The stress concentration zones in the first and second stages have a more obvious symmetry, and the present-day stress concentration zone is located in the center of the syncline basin. (3) The superimposed rock fracture indices are larger in the edge zone parallel to the long axis of the syncline and at the bottom of the syncline, which also indicates a higher degree of structural fracture development at the corresponding locations. Full article

The precise preparation and application of nanomicrospheres is currently an emerging research hotspot in the cutting-edge cross-disciplines. As an important functional material, nanosized microspheres show a broad application prospect in biomedicine, chemical engineering, materials science, and other fields. However, microspheres with good monodispersity are still facing technical bottlenecks, such as complicated preparation process and high cost. In this study, a multistage cyclic dielectrophoresis (MC-DEP) technique is innovatively proposed to successfully realize the high-resolution sorting of submicron microspheres. A dielectrophoresis chip adopts a unique electrode design, in which the electrodes are arranged at the top and bottom of the microchannel at the same time. This symmetric electrode structure effectively eliminates the difference in the distribution of dielectrophoretic force in the perpendicular direction and ensures the homogeneity of the initial state of particle sorting. Three pairs of focusing electrodes are in the front section of the microchannel for preaggregation of the microspheres, and the deflection electrodes in the back section are to realize particle size sorting. After this, the upper and lower limits of particle size are limited by multiple cycles of sorting. The multistage cyclic sorting increases the stability of particle deflection under dielectrophoretic forces and reduces the error perturbation caused by the fluid environment. The experimental results show that the multistage cycling sorting scheme significantly improves the monodispersity of the microspheres, and the coefficient of variation of the particle size is significantly reduced from the initial 12.3% to 5.4% after three cycles of sorting, which fully verifies the superior performance of this technology. Full article

This research explores the dynamic characteristics of composite nano-beams with a hybrid cellular structure (HCS) core, composed of two segments with distinct unit cell configurations, and face sheets reinforced with carbon nanotube (CNT) composites. By considering three-layered sandwich beams with aluminum cores of varying unit cell angles, the study explores a broad spectrum of achievable Poisson’s ratios. The top and bottom face sheets incorporate CNTs, distributed either uniformly or in a functionally graded manner. The governing equations are derived using Eringen’s nonlocal elasticity framework and the modified theory of shear deformation, with solutions obtained via the Galerkin method. A detailed parametric analysis is conducted to evaluate the effects of CNT content, arrangement configurations, hybrid core cellular angles, nonlocal parameters, and slenderness ratio (L/h) on the dimensionless natural frequencies of sandwich nanobeams with hybrid cellular cores. A key contribution of this study is the presentation of natural frequencies for nanobeams with hybrid cellular cores and composite face sheets reinforced with functionally graded CNTs, derived from advanced theoretical formulations. These findings offer new insights into design optimization and highlight the potential applications of hybrid cellular sandwich nanobeams in cutting-edge engineering systems. Full article

This systematic review analyzes and compares the predictive power between traditional financial ratios and cash flow-based ratios in estimating performance. Although traditional ratios of return on assets and debt to equity have received extensive application, cash flow ratios are increasingly valued by their dynamic insights into both liquidity and financial health. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, this review systematically analyzes 21 studies spread across various industries and regions. The results reveal that cash flow ratios usually dominate the traditional metrics during forecasting financial performance, especially in the presence of the use of machine learning models. Among the identified variables of the logistic regression model and gradient boosting model predictors, key indicators are those showing the return on investment, the current ratio, and the debt-to-asset ratio. The bottom line of the findings is that a combination of cash flow and traditional ratios gives a better understanding of a company’s financial stability. These results may serve as a starting point for investors, regulators, and entrepreneurs and may further facilitate informed decisions with a reduced chance of miscalculations that enhance proactive financial planning. In addition, future prediction models should integrate non-financial factors such as governance quality and market conditions to enhance financial health assessments. Additionally, longitudinal studies examining the evolution of financial ratios over time, along with hybrid statistical and machine learning approaches, can improve forecasting accuracy. Integrating cutting-edge analytical tools with the strength of financial metrics gives this study actionable insights that allow stakeholders to understand financial performance in a more nuanced sense. Full article

Single-atom catalysts (SACs) are presently recognized as cutting-edge heterogeneous catalysts for electrochemical applications because of their nearly 100% utilization of active metal atoms and having well-defined active sites. In this regard, SACs are considered renowned electrocatalysts for electrocatalytic O₂ reduction reaction (ORR), O₂ evolution reaction (OER), H₂ evolution reaction (HER), water splitting, CO₂ reduction reaction (CO₂RR), N₂ reduction reaction (NRR), and NO₃ reduction reaction (NO₃RR). Extensive research has been carried out to strategically design and produce affordable, efficient, and durable SACs for electrocatalysis. Meanwhile, persistent efforts have been conducted to acquire insights into the structural and electronic properties of SACs when stabilized on an adequate matrix for electrocatalytic reactions. We present a thorough and evaluative review that begins with a comprehensive analysis of the various substrates, such as carbon substrate, metal oxide substrate, alloy-based substrate, transition metal dichalcogenides (TMD)-based substrate, MXenes substrate, and MOF substrate, along with their metal-support interaction (MSI), stabilization, and coordination environment (CE), highlighting the notable contribution of support, which influences their electrocatalytic performance. We discuss a variety of synthetic methods, including bottom-up strategies like impregnation, pyrolysis, ion exchange, atomic layer deposition (ALD), and electrochemical deposition, as well as top-down strategies like host-guest, atom trapping, ball milling, chemical vapor deposition (CVD), and abrasion. We also discuss how diverse regulatory strategies, including morphology and vacancy engineering, heteroatom doping, facet engineering, and crystallinity management, affect various electrocatalytic reactions in these supports. Lastly, the pivotal obstacles and opportunities in using SACs for electrocatalytic processes, along with fundamental principles for developing fascinating SACs with outstanding reactivity, selectivity, and stability, have been highlighted. Full article

Virtual simulation of high-resolution multi-axis machining processes nowadays plays an important role in the production of complex parts in various industries. In order to improve the surface quality and productivity, process parameters, such as spindle speed, feedrate, and depth of cut, need to be optimized by using an accurate process model of milling, which requires both the fast virtual prototyping of machined part geometry for tool path verification and accurate determination of cutter–workpiece engagement for cutting force predictions. Under these circumstances, this paper presents an effective volumetric method that can accurately provide the required geometric information with high and stable computational efficiency under the condition of high grid resolution. The proposed method is built on a tri-level grid, which applies two levels of adaptive refinement in space decomposition to abolish the adverse effect of a large fine-level branching factor on its efficiency. Since hierarchical space decomposition is used, this multi-level representation enables the batch processing of affected voxels and minimal intersection calculations, achieving fast and accurate modeling results. To calculate the instantaneous engagement region, the immersion angles are obtained by fusing the intersection points between the bottom-level voxel edges and the cutter surface, which are then trimmed by feasible contact arcs determined using envelope theory. In a series of test cases, the proposed method shows higher efficiency than the tri-dexel model and stronger applicability in high-precision machining than the two-level grid. Full article

The milling force plays a pivotal role in CFRP milling. Modeling of the milling force is helpful to explore the changing law, optimize the processing parameters, and then reduce the appearance of defects. However, most of the existing models ignore the effect of the bottom edge. In this paper, the prediction of milling force in CFRP milling processes is taken as the research object. By analyzing the milling mechanism and considering the end milling cutter’s bottom cutting edge, the prediction model of milling force was established. Based on the experimental data and simulation data of milling force, the milling force coefficient was obtained by inverse calculation. Subsequently, the predicted cutting force was compared with the experimental cutting force, showing a maximum error of 14.5%, which is within a reasonable range, and the correctness of the model was verified. Furthermore, combined with the delamination damage and the milling force prediction model, a multi-objective optimization model of milling parameters was established, and the genetic algorithm was used to solve the model. The unidirectional carbon fiber plate with a fiber direction angle of 45° was selected as the optimization example. The minimum delamination damage was obtained under the cutting conditions of a spindle speed of $4903.1569 \mathrm{r}/\mathrm{m}\mathrm{i}\mathrm{n}$, feed rate per tooth of $0.01 \mathrm{m}\mathrm{m}/\mathrm{z}$, and an axial depth of cut of $0.5 \mathrm{m}\mathrm{m}$, and the experimental verification was carried out. The feasibility of the genetic algorithm in CFRP milling parameter optimization modeling was also verified. Full article

Helical grinding is crucial for manufacturing small holes in hard-to-machine composite ceramics. This study introduces a geometric model of undeformed chips to analyze the cutting characteristics of abrasive grains on both the bottom and side edges of the tool. It reveals for the first time that the distribution of cutting grains—pure bottom-edge, pure side-edge, and mixed-edge—is influenced by the tool diameter and eccentricity. A novel calculation method for the distribution range (D_p) of pure bottom-edge grains is proposed, demonstrating that using a tool diameter at or below two-thirds of the target hole diameter effectively eliminates pure bottom-edge grains, improving chip evacuation, reducing chip adhesion, and optimizing cutting performance. Experimental validation on small holes in SiC_p/Al composites (65% volume fraction) confirmed these findings and provides practical guidance for optimizing cutting parameters and tool design. Full article

The study of lithium (Li), gallium (Ga), and rare earth elements (REY) within coal-bearing strata represents a cutting-edge concern in coal geology, ore deposit studies, and metallurgy research. With the rapid advancement of technology and emerging industries, the global demand for Li-Ga-REY has significantly escalated. Several countries worldwide are facing immense pressure due to shortages in Li-Ga-REY resources. Coal-associated Li-Ga-REY depositions have emerged as a pivotal direction for augmenting Li-Ga-REY reserves. To ascertain the enrichment distribution patterns and genetic mechanisms of Li-Ga-REY within the coal-bearing strata of the late Permian Heshan Formation in Wanfu mine, Xian’an Coalfield, Guangxi Province, this study carried out comprehensive testing and analysis on Li-Ga-REY enriched in the mineralized layers within the strata. The Heshan Formation in Wanfu mine presents four layers of Li-Ga-REY-enriched mineralization, labeled from bottom to top as mineralized layers I, II, III, and IV, corresponding to coal seams K5, K4, K3, and K2. These critical metals are predominantly hosted within clay minerals (kaolinite, illite/smectite, and chlorite). The enrichment of critical metals within the Heshan Formation is closely related to terrigenous detrital materials from the Daxin paleocontinent, volcanic detrital materials induced by the Emeishan mantle plume and the Yuenan magmatic arc. The accumulation of Li-Ga-REY and other critical elements within the mineralized layers is the result of inputs from terrestrial and volcanic detrital sources, interactions between peatification and diagenesis stages, and occasionally the input of metal-enriched fluids. In the mineralized layers I, II, and III, the content of lithium oxide (Li₂O) surpasses the boundary grade, and the levels of REY, Ga, and (Nb,Ta)₂O₅ are close to boundary grades, indicating promising exploration prospects. The Wanfu mine in the Xian’an Coalfield can be considered a primary target zone for the exploration and development of coal-associated critical metal resources in Guangxi. Full article

This paper aims to investigate the outlook of energy generation by means of transformation within the context of sustainable energy development. An analysis is conducted to assess the stability of energy systems so to implement cutting-edge energy production models at the national level, with a focus on a contemporary approach to energy modeling. Considering the energy transition and the existing constraints within the energy industry, the model assesses the feasibility of the practical advancement of renewable energy sources. The bottom-up energy model was used to determine how the components of energy development sustainability can be applied until the year 2050. To perform comparison testing with the reference state scenario, the LEAP energy model was used. This instrument was selected because of its ability to provide flexible and advanced options for selecting suitable parameters for energy transformation prediction. A progressive reduction in environmental pollution can be achieved by the deployment of current methods of energy generation by transformation until the year 2050 in Serbia, as indicated by the findings. The research highlights the significance of utilizing green energy sources for the continuing development of energy and the gradual reduction in environmental pollution through value co-creation. Full article