Highlights in Science, Engineering and Technology
Highlights in Science, Engineering and Technology is an open access, peer-reviewed publication series published by Darcy & Roy Press. It aims to publish conference proceedings dealing with all areas of science, engineering and technology.
Soft Robotic Gripper with Tunable Stiffness and Multi-Modal Bending Enhancing Gripping Ability
Soft pneumatic grippers, structures created from soft material like silicone rubber and powered by air pressure, can grip and transfer fragile items safely and stably. These grippers are widely applicable under medical situations, especially during surgery. Other applications include automated laboratory operations, underwater gripping, food delivery, extraterrestrial exploration efforts, etc. However, traditional soft grippers face serious difficulties with gripping objects of different volumes and weights. This study proposed a novel layer-jamming mechanism of tuning the stiffness of soft grippers to increase its weight capacity. The study also proposed a novel bellowed-pipe structure for soft grippers to incorporate dual-mode gripping. The process of gripping was automated through the introduction of a camera and recognition algorithms capable of computing the size and depth of the detected object. Experiments conducted in room conditions, using the variable stiffness mechanism, the gripper could grip objects 120% heavier than without using the mechanism, indicating a significant advancement from traditional soft grippers. Further research could be done with making the gripper smaller and applicable under surgical conditions.
Soft Robotics, Stiffening, Multimodal, Increased Load, Increased Gripping Range.
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A Comprehensive Analysis on Edge Deployment and Optimization of Llms
After years of development, impressive capabilities are demonstrated by various large language models (LLMs) across many fields. Traditionally, cloud appears to be the preferred deployment option for most applications. The remarkable reasoning performance relies on the support of large and continuous computational power. Increased latency, bandwidth consumption overheads, and lack of privacy protections. All of these are the costs that come with cloud deployment and causing it unsuitable for certain scenarios. In order to address these challenges, increasing research interests toward localized deployment of LLMs have prompted. Such deployment also introduces several issues including limited computational capability, memory capacity, and power consumption of edge devices. This paper first provides an overview of different LLM architectures. Then introduces several proposed approaches aimed at addressing the issues mentioned. Multiple directions are covered, including algorithm-level techniques such as quantization, lightweight or distilled models, and MoE-based architectures; hardware acceleration optimization; algorithm–hardware co-design approaches; and edge–cloud collaboration like split inference strategies. A range of studies are referenced to provide evidence and analysis for the respective approaches. Together it provides insights into current research status, difficulties, and potential opportunities in the related field.
LLMs; edge deployment; quantization; light-weight models; edge-cloud collaboration.
The Development and Prospect of Shoulder Flexible Exoskeleton Structures
The emergence of flexible exoskeletons has provided new ideas for the treatment and rehabilitation of various diseases. The development of shoulder flexible exoskeleton structures is a topic of great research value and potential in the field of exoskeleton research. This paper aims to analyze and prospect the development of shoulder flexible exoskeleton structures. By comparing and analyzing the representative achievements of each key technology in the structure and support system, drive and transmission system, and sensing and control system, the advantages of different achievements are derived. By reviewing the development process of shoulder flexible exoskeletons, it is proposed that flexibility, lightweight, and intelligence are the development trends of shoulder flexible exoskeletons. It is also suggested that a standardized evaluation system should be established to facilitate researchers to intuitively experience the performance of different products. By focusing on the existing problems, it is pointed out that the key points of research on the flexible exoskeleton structure of the shoulder mainly lie in improving the mechanical structure of the flexible exoskeleton, coordinating the driving mode, human-computer interaction, and motion intention recognition, as well as the comfort of use.
Shoulder flexible exoskeleton, mechanical structure of flexible exoskeleton, flexibility.
Research on an Optimization Model for Multi-Objective Smoke Screen Deployment by Drones Based on Genetic Algorithms and Simulated Annealing
This paper proposes a multi-layer optimization framework for missile concealment using smoke screens deployed by UAVs. It focuses on coordinating single-UAV single-missile and single-UAV multiple-missile operations through genetic algorithm-based optimization, while incorporating a hybrid solution combining simulated annealing and entropy-weighted evaluation in multi-UAV multiple-missile scenarios. First, three-dimensional dynamic trajectories for missiles, UAVs, warheads, and smoke cloud centers are established alongside a “three-step effective concealment” constraint, constructing a nonlinear model targeting effective concealment duration. Second, genetic algorithms perform encoding, crossover, mutation, and adaptive iteration to solve optimal release strategies for single-UAV-single-missile scenarios, then extend to multi-missile temporal coordination. Finally, integer programming provides initial allocations, simulated annealing searches within neighborhoods, and entropy weighting assigns multi-criteria scores. An embedded genetic algorithm evaluates strategy performance. This model rapidly approximates global optima under strong nonlinearity and coupled constraints, enhancing both effective shielding duration and resource allocation efficiency. It offers scalability, robustness, and engineering feasibility.
Genetic algorithm; simulated annealing algorithm; entropy weight evaluation method.
Bio-Signal Controlled Exoskeleton for Accurate Elbow Rehabilitation
To address the limitations of current elbow rehabilitation exoskeletons—namely insufficient force-control accuracy, low active user engagement, and poor adaptability to individual needs—this work develops a precision-controlled exoskeleton system based on biological signal perception. The system acquires muscle activity through surface electromyography (sEMG) sensors and identifies movement intentions using a convolutional neural network (CNN). A differential transmission mechanism is employed to drive elbow flexion–extension and forearm pronation–supination, enabling two degrees of freedom. Experiments were conducted with four healthy subjects to compare sEMG signals (RMS) and primary joint torque between a free mode and an assistive mode under three forearm postures (neutral, pronation, and supination). Results show that, in assistive mode, the RMS of major upper-limb muscles decreased by an average of 38.53 ± 11.98%, and primary joint torque decreased by an average of 58.5 ± 17.27%. The brachioradialis exhibited the largest RMS reduction in the neutral posture (54.76 ± 16.69%), while the supination posture resulted in the greatest torque reduction (66.2 ± 15.34%). These findings demonstrate that the proposed system effectively reduces muscle activation and voluntary effort, validating its effectiveness in rehabilitation training and the stability of human–robot cooperative control.
Elbow exoskeleton; Electromyography (EMG); Movement intention recognition; Convolutional neural network (CNN); Assistive control; Rehabilitation training.
Current Status and Trends in Surgical Robot Development Across Different Operating Environments
The application of surgical robots has enhanced surgical precision and resolved previously challenging issues in operations, making it one of the most researched topics worldwide. This paper elucidates the significance of selecting surgical robots tailored to the characteristics of different surgical environments. This paper introduces that the application of surgical robots in the abdominal surgery environment can make up for the shortcomings of traditional surgery and perform long-distance surgery. The application of a frameless stereotactic surgery robot in neurosurgery has high precision, and the controllability of the operation process is effectively enhanced through the dynamic calibration mechanism. The surgical robot applied in the microsurgery environment can improve the operation accuracy of the surgery through the functions of motion scaling and tremor filtering. However, the current surgical robot still has the limitations of low penetration, limited tactile feedback, and a long user training cycle. In the future, the rational application of AI and the targeted development of the functions of surgical robots according to the characteristics of the corresponding surgical environment are the key to expanding the application of surgical robots.
Surgical Robot; Surgical Environment; Precision.
Nanomaterial-Enabled Sensing for Coupling of Implantable Bcis and Prosthesis
Amputation caused by trauma, vascular diseases, etc., has created a global demand for high-performance prosthesis technology. Traditional electromyographic prostheses are limited by low signal fidelity and a lack of natural feedback, while implantable brain-computer interfaces still face bottlenecks such as insufficient signal stability and biocompatibility. Nanomaterials offer new possibilities to break through this dilemma. This article reviews the role of nanomaterial-enabled sensing technology in the collaborative control of implantable brain-computer interfaces and neural prostheses. The key mechanisms in improving electrochemical performance, matching mechanical flexibility, and regulating biological activity are analyzed emphatically. Through the representative studies of graphene, MXene, liquid metal, and biological hybrid interfaces, the significant advantages of nanostructures in reducing impedance, improving signal-to-noise ratio, and long-term stability are demonstrated, and the performance gain and closed-loop control potential in cross-scale systems are discussed. This paper summarizes that implanted electrodes can achieve a high signal-to-noise ratio, low delay, and multi-channel stable acquisition, but the problem of signal attenuation and biocompatibility is still prominent under long-term implantation conditions. In the future, collaborative optimization at the material and system levels is still needed. At the same time, this paper points out the emerging directions such as self-healing electrodes, bionic closed-loop systems, and organoid interfaces, which will promote brain-computer interfaces to be clinically feasible and natural interaction.
Implantable brain-computer interfaces (BCI); Nanomaterials; Neural Prosthesis; Closed-loop control.
A Critical Analysis on FPGA–CGRA Co-Design for Energy-Efficient Edge AI Systems
With the advancement of artificial intelligence (AI) in Internet of Things (IoT) devices, drones, wearables, and autonomous robots, the need for real-time processing edge AI processors has grown significantly. Architectures like field-programmable gate arrays (FPGAs) and coarse-grained reconfigurable architectures (CGRAs) have advancements in a particular field, but the stringent requirements of latency, power, and performance may not be met, respectively. Existing studies typically analyze FPGA-CGRA in isolation, leaving a limited understanding of the methodology and functionality of the hybrid architecture. Therefore, this review examines how hybrid FPGA-CGRA computing addresses problems like power efficiency and flexibility and found that it could achieve 1.93x higher peak performance and 48.5% area saving compared to a singular architecture alone. However, its limitations also need to be considered, such as performance overlay and high resource consumption. This research provides important insights for designing next-generation edge computing accelerators that balance flexibility, efficiency, and real-time processing needs.
FPGA, CGRA, Co-Design, Energy-efficient.
Design and Simulation of an Underactuated Finger Rehabilitation Exoskeleton based on Bionic Kinematics
Nowadays, stroke is the leading cause of death and disability in China, and the disability rate exceeds 80%. Approximately 80% of patients have upper limb functional disorders, and the impairment of fine hand movements is particularly significant. The effect of traditional rehabilitation treatment is limited, and the existing finger exoskeletons have problems such as insufficient bionics and poor adaptability to daily scenarios, which restrict the clinical rehabilitation effect. In response to the problem that finger rehabilitation exoskeletons can achieve a high degree of bionics and be close to daily life, based on the bionic principle of the four-bar linkage mechanism, a design scheme for an under-actuated finger rehabilitation exoskeleton with a serial topological transmission of connecting rods is proposed. The device uses an aviation aluminum alloy frame. The stiffness of the key load-bearing parts reaches 18 GPa, and the weight is less than 200 g. Compared with traditional stainless steel materials, the mass is reduced by 42%. Simulate the coordinated relationship between adjacent phalanges during the flexion and extension movements of human fingers, achieve multi-joint linkage driven by a single power source, and it is suitable for the rehabilitation of hand motor function in stroke patients. Based on the patients' grasping needs in various life scenarios, kinematic simulations and analyses of grasping small balls made of rubber, oak, and stainless steel were carried out. The feasibility of the design of an underactuated finger rehabilitation exoskeleton based on bionic kinematics was verified.
Exercise Enhancement, Exoskeleton, Underactuation, Mechanism Design, Simulation Analysis.
Progress in Robots Driven by SMA Actuators and Their Control
With the popularization of mechanical automation, informatization, and intelligence have become the development direction of future mechanical-related majors, and research related to robots has become a hot topic nowadays. Traditional robots often suffer from shortcomings such as poor adaptability, weak interaction capabilities, and limited functionality. Therefore, some scholars have researched emerging materials represented by Shape Memory Alloy (SMA). The flexibility, high power density, and other characteristics of SMA make it extremely promising for robotic applications. This article primarily introduces the current development status of robots driven by SMA actuators and reviews relevant research in recent years, aiming to explore their future applications. However, most current SMA actuator designs still have significant limitations. This article will summarize some of the more cutting-edge robots driven by SMA actuators and their control methods, analyze the corresponding experimental data in detail, summarize the degree of improvement made to SMA actuators in various studies, and strive to find the optimal solution, providing a plan for the research of SMA actuators.
Compliant Control of an Upper Limb Rehabilitation Robot Based on Impedance Design
Robot-assisted therapy is an essential rehabilitation method to regain motor function in upper limb impairment after neurological events such as stroke. The most challenging and problematic issue in this field is to realize safe and natural human-robot interaction. Conventional robots, which are generally controlled by rigid position controllers, cannot be compliantly adjusted according to the patient's voluntary movement or spasm. The appearance of high interaction forces is also a potential cause of secondary damage. This is a big research gap that requires further research on advanced compliant control. This paper is devoted to addressing this problem by developing an adaptive impedance controller to realize compliant control for an upper limb rehabilitation robot. The dynamic model of the robot is established in the paper, and the adaptive impedance control law is formulated. Then the parameters of the impedance controller can be adjusted in real-time based on interaction forces. To validate the effectiveness of the proposed controller, several simulation analyses under different scenarios are conducted, such as tracking a predefined trajectory without any external interference and with interaction forces generated by simulated patients. The simulation results indicate that besides the controller can guaranteeing stable and accurate tracking, the controller also has a good compliance performance, i.e., the interaction forces decrease significantly when external disturbances from patients appear. The effectiveness and superiority of the adaptive impedance control design are verified by the simulation results. The physical rehabilitation system based on the adaptive impedance control design has a good theoretical reference and simulation basis.
Upper Limb Rehabilitation Robotics, Adaptive Impedance Control, Impedance Control.
Simulation and Analysis of an Adaptive Manipulator Based on Machine Learning
This study takes the PUMA560 manipulator as the research object, selects its first three rotating joints to construct a 3-degree-of-freedom (3-DOF) manipulator system, and aims to improve the control accuracy of the manipulator and environmental adaptability. First, the Denavit-Hartenberg (DH) parameter method is used to establish the manipulator’s kinematic model; the MATLAB Robotics Toolbox is employed to define the link coordinate system, joint angles, link lengths, and other DH parameters, and a velocity ellipsoid is constructed to analyze the motion characteristics of the end effector. In the trajectory planning stage, the Joint Trajectory Planning (JTRAJ) function (for smooth interpolation in joint space) and the Cartesian Trajectory Planning (CTRAJ) function (for linear path interpolation at the end effector) are compared, and finally, the JTRAJ function is selected to plan the target path. To achieve precise control of the manipulator, a PID (Proportional-Integral-Derivative) control simulation model based on Simulink is built. Simulation results show that compared with manual parameter tuning, the PID control optimized by Genetic Algorithm (GA) has a smaller error fluctuation range, and the error tends to be stable at the end of the simulation, significantly improving the manipulator’s control robustness and trajectory accuracy. This study realizes the effective integration of machine learning and traditional control algorithms, providing a feasible solution for the optimization of manipulator adaptive control; future research can further explore the influence of parameter ranges and fitness function definitions on control effects, and improve data horizontal comparison to deepen the research.
Machine Learning; PID; 3-DOF Manipulator; Genetic Algorithm.
The Advanced Control Technologies of Lower Limb Exoskeleton Rehabilitation Robots
The lower limb exoskeleton rehabilitation robots, a common medical device, are designed to treat people with lower limb disorders, have been widely deployed across the medical sector. In this review, the human gait is analyzed initially since this is the foundation of the lower limb exoskeleton rehabilitation robots research. Through this analysis, the clear relationship is illustrated between the magnitude and direction of support force provided by the lower limb exoskeleton rehabilitation robot to each joint and the control technologies. Then the following discussions will focus on the two advanced control technologies, which are the key to the lower limb exoskeleton rehabilitation robots, called position control and impedance control, respectively. These two control technologies are currently applied in multiple fields, which are an integral part of modern life, and the results of this study are promising for related future research on lower limb exoskeleton rehabilitation robots. This review further provides a theoretical framework for optimizing control strategies and enhancing human–robot interaction efficiency in lower limb rehabilitation systems.
Advanced control technologies, lower limb exoskeleton rehabilitation robots, human gait.
Paradigm Shift, Technical Challenges, And Future Path of Exoskeleton Human-Computer Interaction Control Model
With the gradual development of exoskeleton robot hardware, the research focus should be transferred to the control model. The current field of exoskeleton control systems is undergoing a paradigm shift from traditional human-computer interaction to human-computer symbiosis. This research focuses on the control model and control strategy of an exoskeleton robot. Through a systematic review of the literature, this paper divides the current control model into four clear control paradigms: brain-less control, perceptual control, predictive control, and symbiotic control, and prospects the future human-computer interaction mode of exoskeleton. At the same time, the core characteristics, typical cases, and limitations of each paradigm are analyzed, and the four trends of human-computer symbiosis are summarized. The future development path of exoskeleton based on artificial intelligence, brain-computer interface, and new sensing technology is outlined. Brainless control can not adapt to individual differences and real-time changes, ignoring the real-time state of people. Perceptual control cannot predict or look forward to motor intention. Predictive control is complex in calculation, highly dependent on the model and data, and mostly in the laboratory stage. In the future, a close coupling and bidirectional communication man-machine relationship will be formed to form a man-machine intelligent unity.
Exoskeleton, Control Strategy, Human-Computer Interaction.
Robust Parameter Design Based on Functional Latent Gaussian Processes and Its Application in Additive Manufacturing
For the robust parameter design problem of functional responses, a novel robust parameter optimization model is proposed within the functional latent Gaussian process (LFGP) modeling framework. First, maximum likelihood estimation is employed to obtain the required hyperparameters for fitting the LFGP model. Second, leveraging the characteristics of the LFGP model, we construct an objective function that fully accounts for response variability, thereby establishing an optimization model for functional responses. Finally, we employ a genetic algorithm (GA) for global optimization to obtain optimal input parameter settings. Results from an additive manufacturing case study demonstrate that this method achieves superior prediction accuracy and optimization performance for functional data compared to traditional Gaussian process functional regression and principal component analysis models.
Gaussian Process, Robust Parameter Design, Functional Response, Additive Manufacturing.
Classification and application of wind tunnel experiment
The main purpose of this paper is to introduce the wind tunnel experiment in different aspects. This paper firstly presents the designs and classifications of wind tunnels. The wind tunnels will be classified as low-speed wind tunnels, aeroacoustic wind tunnels and subsonic wind tunnels. Under the classification of low-speed wind tunnels, there are open return wind tunnels and closed-circuit wind tunnels. The structural designs of topology optimization, topography of optimization, size optimization, free size optimization are introduced and compared. Traditional and modern measurements of the fluid are listed and given detailed examples. The applications of wind tunnel design in stress, dynamic and aeroelastic analysis, aerospace, cars and high-speed trains and environment and buildings will be introduced. The paper will analyze current challenges such like the reliability of wind tunnel data validating and calibrating numerical models, achieving sufficiently low turbulence intensity (TI) and background noise levels and similitude constraints when scaled models being tested. At last, the development trends in this field ‘ll be introduced and future outlook will be predicted.
Wind Tunnel Experiment, Design, Low-Speed Wind Tunnel.
Impact of Powertrain Systems on Automobiles
The powertrain system, as the important component of automobiles, profoundly influences vehicle performance, design, and environmental sustainability. This paper provides a comprehensive analysis of the impact of powertrain systems on modern vehicles, examining the evolution from traditional internal combustion engines (ICE) to hybrid, pure electric, and emerging powertrains such as hydrogen fuel cells. It explores how powertrain design dictates key performance metrics including acceleration, top speed, energy efficiency, and driving refinement, while also shaping vehicle morphology, structural layout, and aerodynamic characteristics. Furthermore, the study highlights the role of lightweight materials, intelligent energy management, and integrated design in enhancing overall vehicle efficiency and sustainability. The paper also discusses future trends, including the deep integration of electrification and intelligence, advancements in lightweighting and green manufacturing, and the challenges of achieving full lifecycle carbon neutrality. It concludes that the continued innovation and optimization of powertrain systems are essential for meeting diverse market demands and advancing toward a clean, intelligent, and sustainable automotive industry.
Powertrain System, Automobile Performance, Vehicle Design.
The History of Liquid Rocket Fuel Engine
This paper discusses the development of liquid rocket fuel engine, fuels and fuel tanks structural design. From aerodynamic theory to experiment, both Tsiolkovsky's theoretical formula and Goddard's first test flight has made outstanding contributions. On this basis, the rocket can be truly utilized. The V-2 rockets from World War II, the various large rockets of the United States and the Soviet Union during the Cold War, as well as the modern reusable rockets, all had their different roles in different periods. In terms of fuel, the development from alcohol to kerosene to liquid oxygen and finally to liquid methane demonstrates the significance of reusable rockets in commercial spaceflight today. This is to achieve greater controllability and storage capacity. The aerospace fuel tank aims for lightweight and reusability. It features multiple layers of insulation and active cooling, and uses composite materials instead of metals to ensure the spacecraft's deep-space travel.
Liquid Rocket Engine, Fuels and Propellants, Fuel Tanks Structural Designs, Reusable Rocket, Commercial Spaceflight.
Structural deformation prediction of vehicle-mounted radar based on deep learning
The vehicle-mounted radar antenna boasts a relatively large size, making its structure susceptible to significant wind forces under strong winds. Additionally, since antennas are typically installed on the rooftops or other elevated positions of vehicles, the large wind resistance area may lead to structural deformation. Therefore, this paper proposes a novel approach. Firstly, this paper utilizes SolidWorks to model the antenna's back frame, beams, and element array, employing high-strength aluminum alloy materials to strike a balance between lightweightness and stiffness requirements. Secondly, this paper imports the model into ANSYS Workbench to simulate the pressure exerted by wind speeds ranging from 5 to 35 meters per second, selecting deformation data from 480 monitoring points (442 on the crossbeam and 38 on the back frame). Finally, this paper constructs a strain-displacement BP neural network model. The experimental findings reveal that: ① The deformation of the antenna intensifies with increasing wind speed, with a 2.5-fold increase at 25 meters per second compared to 5 meters per second; ② The predictive accuracy of the model enhances with wind speed, achieving the smallest error at 25 meters per second (a 70% reduction compared to 5 meters per second), with an overall prediction accuracy exceeding 98%; ③ The locations with larger errors vary across different wind speeds, concentrating in specific areas during high-speed winds.This method addresses the challenge of monitoring antenna deformation in strong enhances the precision of health monitoring for vehicle-mounted radar antenna systems but also offers more accurate data for future structural monitoring and the design of vehicle-mounted antennas.
Vehicle-mounted radar, BP neural network, health monitoring, structural deformation.
Research Outline and Abstract of Intelligent Control-Based Water Body Health Prediction and Management
The fundamental point of the ecological balance in water bodies and the safety of drinking water is the health of water bodies. The traditional models for managing water quality are no longer effective in dealing with the environmental challenges that are now more complex due to their lagging and low efficiency. This paper tries to examine and implement the use of intelligent technologies in building an intelligent water body health management system that would encompass the prediction, early warning, and decision support. On the one hand, the system of a multi-dimensional water body health assessment that involved physical, chemical, and biological indicators was created, and the need to standardize the data was explained. Then three fundamental intelligent prediction algorithms, namely BP neural network (BPNN), fuzzy logic, and support vector machine (SVM), were thoroughly discussed, explaining their working mechanism and merits and demerits in water quality prediction. The above models were trained and validated through real monitoring data for a given reservoir using a case study. The findings revealed that the combined model indicated a high degree of benefit in the accuracy of prediction and stability. Based on this, a three-layer intelligent management system architecture including the perception layer, platform layer, and application layer was designed, achieving a management closed loop from data collection, intelligent prediction to decision support. The research results not only provide efficient and forward-looking technical means for water environment supervision but also lay a solid theoretical and practical foundation for achieving the grand goal of "smart water management".
Water body health, Intelligent prediction, BP neural network, Fuzzy control, Support vector machine.
Aerodynamic Design and CFD Simulation in Formula 1 Underbody Optimization
Since the modern era, aerodynamic design has become an indispensable element of automotive engineering, particularly in motorsport. Formula 1 stands as a prime example of aerodynamic design pushed to its absolute limits. Through meticulous aerodynamic configuration, Formula 1 cars generate immense downforce during races, thereby enhancing cornering speed and stability. In Formula 1, the underbody alone contributes more than half of the car’s total downforce. Consequently, the aerodynamic design of the racing car’s underbody plays a crucial role in its on-track performance. This article explores the principles of CFD simulation, including governing equations, turbulence models, and boundary condition settings. It examines diffuser design optimization and the degradation of aerodynamic performance under wake effects using CFD simulation methods. Furthermore, it discusses the limitations of CFD modelling and future directions for innovation in aerodynamic design.
Aerodynamic Design, CFD Simulation, Downforce Generation, Underbody Optimization.
Optimization Pathways for Exoplanet Atmospheric Spectroscopy Detection
Earth is currently facing severe environmental degradation, including pollution, climate anomalies, and the depletion of natural resources, which have prompted humanity to look beyond our planet for potential habitable worlds. Exoplanets within the habitable zone, such as K2-18b, may possess liquid water, a stable atmosphere, and organic molecules that could sustain life. The James Webb Space Telescope (JWST) has provided groundbreaking observations through transit spectroscopy revealing the presence of water vapor and possible biosignatures such as dimethyl sulfide (DMS), a compound commonly associated with biological processes on Earth. However, JWST’s data accuracy is still hindered by three major challenges: thermal and instrumental noise, stellar activity interference including flares and starspots, and limited spectral databases that fail to fully replicate cosmic conditions. To address these limitations, deep learning methods can improve signal extraction, HRCCS technology can enhance spectral precision, and quantum computing simulations can generate more realistic atmospheric spectra. Future interdisciplinary integration will advance exoplanetary research toward reliable life detection.
Exoplanet Atmosphere Detection, James Webb Space Telescope (JWST), Transit Spectroscopy, Biomarkers, Deep Learning Noise Reduction Technology.
Finite Element Simulation-Based Analysis of Electromagnetic Properties of Biological Tissues on Transmission Performance of Implantable Wireless Charging Systems
Wireless charging technology for implantable medical devices has received significant consideration due to its non-contact property. However, its transmission efficiency and safety are deeply influenced by the electromagnetic characteristics of human body tissues. To quantify this effect, this study utilizes ANSYS Maxwell software to build up a simulation model that includes the coil and human body tissue based on finite element analysis and systematically analyzed the working mechanisms of conductivity, permeability, permittivity and the mechanical structure of the coil on determining the magnetic coupling coefficient. The results have shown that, the conductivity of tissues and the misalignment of coil are the main reasons that leads to the decrease of k, while the influence of permittivity in a magnetic coupling dominant mechanism has a negligible impact. Incorporating ANSYS Simplorer to conduct a circuit-level simulation, this study further evaluates the final transmission efficiency and risks for tissue heating of the system, and certified the appropriate range of working frequency (0.1MHz-10MHz) reconciles both high efficiency transmission and biogogical safety. This study provides essential evidence of design and data support for optimizing the transmission coil and selecting the frequency for implantable medical devices of wireless power transfer system.
Wireless Power Transfer, Magnetic Coupling Coefficient, Implantable Medical Devices, Biological Electromagnetic Properties, Finite Element Analysis.
Experimental Validation of a Theoretical Model for Sphere Levitation in a Vertical Turbulent Air Jet
The study focuses on the levitation of a sphere in a vertical turbulent air jet, a well-known phenomenon involving the balance between the fluid drag force and gravitational weight. The purpose of measuring the equilibrium levitation height was to experimentally confirm the predictions made by the theoretical model. This model combines turbulent jet theory with existing drag coefficient equations. Spheres of different masses were suspended in the jet of a hair dryer, and their positions were measured using video analysis. By solving the force balance equation, the theoretical model was constructed. The drag force was determined using the centerline velocity of the jet, which follows a decay law from a virtual origin. The results confirmed the expected trend that the levitation height decreases as the sphere’s weight increases. However, the measured heights were lower than the predicted values. The variations in results were mainly due to flow instabilities at the jet source and the assumed location of the virtual origin, both of which affect the velocity profile. According to the thesis, while ideal models provide a qualitative understanding, their quantitative accuracy is limited by the complexity of real-world flow. To improve the experiments, a more stable flow source should be used. Additionally, direct measurement of the flow field using Particle Image Velocimetry (PIV) and the use of Computational Fluid Dynamics (CFD) simulations may be explored.
Turbulent jet, Sphere levitation, Drag force, Force balance model.
Brief Description of Wing Structure and Materials
This article systematically elaborates on the key technologies and development trends of aircraft wing structure optimization design. The article first points out that, in the context of continuous growth in air transportation volume and increasingly strict environmental requirements, the optimization design of the wing, as the core aerodynamic and load-bearing structure, is of decisive significance for enhancing the economic efficiency, safety, and environmental friendliness of aircraft. The article discusses from multiple dimensions including design theory, material application, manufacturing process and engineering practice. At the design level, it focuses on analyzing core theories such as aerodynamic structure coupling, force transmission path, strength and stiffness, and aerodynamic elasticity. At the material level, it traces the evolution path from traditional metal materials to advanced composite materials (such as CFRP) and even intelligent materials, emphasizing the core advantages of composite materials in achieving lightweighting, long lifespan and functionalization. At the manufacturing and optimization level, it explores how advanced technologies such as additive manufacturing, topology optimization, lattice structure and digital twin can drive the development of wings towards structural-function integration and digital design and manufacturing. Through case studies such as the Boeing 787, Airbus A350 and new-generation unmanned aircraft, the article verifies the engineering effectiveness of the aforementioned theories and technologies, and points out that green materials and circular design for sustainable aviation are important directions for future development. Overall, wing design is a deeply interdisciplinary field. In the future, it will surely integrate new materials, new technologies and intelligent technologies, and continue to evolve towards lighter, stronger, smarter and more environmentally friendly directions.
Wing Structural Design, Composite Materials, Lightweight Design, Aeroelasticity, Topology Optimization, Additive Manufacturing.
The Development History of Planes Engine
The development of jet engines represents one of the greatest achievements in modern engineering, reflecting humanity’s constant pursuit of speed, efficiency, and innovation. From the early piston engines that first lifted aircraft into the sky to today’s advanced turbofan and combined-cycle propulsion systems, the evolution of aircraft engines has continuously reshaped transportation, economics, and defense. Piston engines, though mechanically simple and reliable, were limited in speed and altitude, paving the way for turbojets in the 1940s, which enabled supersonic flight. As aviation demand grew, turbofan engines emerged, offering a balance between power, fuel efficiency, and noise reduction, while turboprop engines became essential for regional and short-haul aircraft due to their superior economy. In recent years, combined-cycle engines have opened new frontiers in hypersonic and reusable aerospace propulsion. At the same time, computational tools such as Computational Fluid Dynamics (CFD) and thermodynamic modeling have revolutionized engine design and optimization, accelerating innovation. Looking forward, with continuous breakthroughs in materials, digitalization, and intelligent control, jet engines will become even cleaner, safer, and more efficient, continuing to drive the progress of human civilization.
Jet Engine, Piston Engine, Turbofan, Turboprop.
Comparative Analysis and Development Strategies for Far-Field Wireless Charging Technologies
Since its inception, wireless charging technology has embodied humanity's aspiration to break free from cable constraints and achieve a seamless energy supply. However, mainstream standards like the electromagnetic induction-based Qi standard face critical limitations: their effective charging range typically spans merely a few millimeters to centimeters, requiring strict alignment between transmitter and receiver. This "near-field" charging mode essentially requires physical proximity, falling short of the ideal of truly seamless charging enabled simply by entering a room. To overcome these spatial constraints, research has shifted towards far-field wireless power transfer (WPT), which enables energy delivery over distances ranging from centimeters to meters. This paper goes beyond a simple overview; it provides a systematic comparative analysis of the principal far-field methods, namely magnetic resonance coupling and directional electromagnetic radiation. It meticulously examines their respective operational principles, advantages, disadvantages, and suitability for different application scenarios. Building on this analysis, the paper discusses potential development strategies and system-level optimization approaches. The findings aim to offer a scientific basis and technical guidance for the future advancement and practical deployment of this transformative technology.
Far-field wireless charging, Magnetic resonance coupling, Directional electromagnetic radiation, System optimization, Comparative analysis.
Comparison of Traditional and Alternative Fuel Engines
Over the past one hundred years, traditional engine have an undeniable impact on the development of human civilization.It is precisely because of the invention of traditional engines that significant breakthroughs have been achieved in many fields. Nevertheless, the use of them contribute large amount of greenhouse gas, such as carbon dioxide. The emission of these gas significantly deteriorate global environment. Additionally, due to the excessive reliance of humans on traditional engines, a large amount of fossil energy has been consumed. The fuels used in traditional engines are mostly non-renewable fossil energy. Therefore, the use of traditional engines has always been detrimental to the sustainable development of humanity in the future. In response, alternative fuel engine (hybrid engine,battery electric engine,fuel cell engine), have developed by people. As time went by and with the development of the times, their appearance gradually replaced the use of traditional engines.In this era where both traditional engines and alternative fuel engines are indispensable, this article focuses on the analysis of their working principles, performance comparisons, advantages and disadvantages comparisons, as well as emissions comparisons.
Traditional engine, comparison, alternative fuel engine, emission.
Research on Issue of NOx Emissions of Diesel Engine
Diesel engine shows higher thermal efficiency than gasoline engine. However, with the effect of emission of Nitrogen Oxide (NOx), diesel passenger vehicles are difficult to gain market share. The Volkswagen diesel emissions scandal that occurred in 2015 undoubtedly sent diesel vehicles to the bottom of the market. Just the issue of NOx emissions alone has plunged diesel vehicles into a crisis of trust. It indicates that the public has zero tolerance for NOx emissions. NOx emissions really have lots of harmful effects on human beings and environments. If diesel vehicles try to regain public favor, issue of NOx emissions must be solved. This article focuses on the specific hazards caused by NOx emissions from diesel vehicles. And give a brief introduction of principle of generation of NOx. Reducing the emission of nitrogen oxides is the key to solving the problem. Now, we need some feasible solutions to reduce the content of nitrogen oxides in the exhaust emissions from diesel vehicles. This article will introduce some potentially feasible solution, which were named as Selective Catalytic Reduction (SCR) and Selective Non-Catalytic Reduction (SNCR).
Diesel engine, NOx emissions, SCR; SNCR.
The Current Status and Future Development of Jet Engines
Jet engines underpin global air mobility but face mounting pressure to cut climate and noise impacts without compromising safety, reliability, and cost. Recent advances—higher overall pressure ratio and turbine inlet temperature, ceramic-matrix composites, lean-burn combustors, chevron nozzles, and digital engine health management—have incrementally lowered specific fuel consumption (SFC) and community noise. In parallel, research is accelerating on Sustainable Aviation Fuels (SAFs), hydrogen (H₂) combustion and fuel-cell hybrids, open-rotor/open-fan architectures, adaptive/variable-cycle engines, and pressure-gain combustion (PGC) using rotating/deflagration detonation. This paper reviews jet-engine fundamentals and surveys peer-reviewed findings from recent academic literature on hydrogen combustor performance and NOx control, open-rotor aeroacoustics, ceramic-matrix composites for hot-section durability, hybrid-electric feasibility, and PGC thermodynamic benefits. We analyze trade-offs and certification barriers, quantify efficiency/emissions levers (bypass ratio, OPR, TIT, combustor technology), and identify research priorities that could enable deep decarbonization by mid-century while maintaining performance and safety. Furthermore, additional discussion is provided on regional hybrid-electric aircraft trials, exergy analyses of SAF blends, and sociotechnical adoption barriers, expanding the scope to more than 3000 words for a comprehensive academic treatment.
Jet engine, sustainable aviation fuel, hydrogen, open-rotor, pressure-gain combustion.