Global Particle Physics Excellence Awards

Introduction Microwave plasma technology has shown significant promise in laboratory-scale applications, particularly in material processing, environmental control, and advanced energy systems. However, when scaled to industrial levels, the increase in microwave power often alters the plasma characteristics in complex ways, affecting the stability and efficiency of the system. A deeper computational understanding of these electromagnetic interactions becomes essential for bridging the gap between controlled laboratory success and industrial scalability. Challenges in Power Scaling of Microwave Plasma Systems As microwave power is increased, electron density in the plasma rises significantly, resulting in higher electrical conductivity. While this enables stronger plasma generation, it also introduces challenges such as higher reflection losses, reduced efficiency, and nonlinear plasma behavior. Understanding these limitations is crucial for preventing performance deterioration during l...

Introduction The increasing complexity of modern vehicles has led to a rapid rise in fault occurrences, creating an urgent need for accurate and intelligent fault prediction systems. Traditional diagnostic models often fail to capture the intricate correlations among faults, leading to reduced prediction accuracy. To address this challenge, deep learning-based approaches have emerged as powerful tools for analyzing large-scale vehicle fault data. In this study, we introduce a collaborative fault prediction model that integrates multiple attention mechanisms to capture fault relationships and predict the likelihood of future failures with higher precision. Motivation for Vehicle Fault Prediction The automotive industry faces significant challenges in ensuring vehicle safety, performance, and reliability. Unexpected faults not only cause costly breakdowns but also pose risks to driver and passenger safety. Current fault diagnosis methods primarily focus on isolated events and fail to acc...

Introduction Cross-domain fault diagnosis for rolling bearings has emerged as a critical research focus in the field of intelligent maintenance and mechanical system health monitoring. Traditional diagnostic methods often struggle when confronted with data shifts across different domains, leading to significant performance degradation. The growing demand for robust and accurate fault detection techniques necessitates the development of innovative approaches that not only align feature distributions effectively but also handle noisy conditions with resilience. In this context, the introduction of the Attention-Enhanced Residual Network (AttenResNet18) offers a transformative solution by combining advanced neural network architectures with adaptive distribution alignment mechanisms, thereby addressing key limitations in existing domain adaptation strategies. Challenges in Cross-Domain Fault Diagnosis A major challenge in cross-domain fault diagnosis is the distribution mismatch that o...

Introduction Superconducting magnetic levitation (Maglev) devices have attracted significant research attention due to their high precision, non-contact support, and frictionless motion. The performance of such systems largely depends on the rotor’s ability to achieve stable high-speed rotation while resisting external disturbances. To ensure this stability, the suspension current plays a critical role, as it directly influences the levitation force and disturbance resistance of the rotor. This study investigates the suspension current characteristics, providing a systematic analysis of its role in the optimization of superconducting magnetic levitation devices. Structural Framework of Superconducting Magnetic Levitation Systems The structural design of superconducting magnetic levitation systems determines how effectively the rotor interacts with the magnetic field. A detailed understanding of coil placement, superconducting materials, and support mechanisms is crucial for minimizing ...

Introduction The Best Committee Member Award is a prestigious honor recognizing individuals who have shown exceptional dedication, fairness, and leadership within academic and research committees. This recognition highlights the vital contributions of those who guide, evaluate, and support research, ensuring that excellence and integrity remain at the forefront of academic and professional endeavors. Role of Committee Members in Research Committee members serve as the backbone of research progress by evaluating proposals, assessing projects, and providing valuable insights to ensure scientific quality. Their role extends beyond supervision; they influence the direction of research, encourage innovation, and safeguard ethical practices, which ultimately advances both education and professional development. Leadership and Professionalism Strong leadership and professionalism are key qualities celebrated through this award. The Best Committee Member demonstrates an ability to manage respo...

Introduction The development of assistive mobility devices has undergone significant transformation in recent years, moving from traditional manual and joystick-controlled wheelchairs to more intelligent, user-centric systems. This research proposes a novel electric wheelchair controlled by surface electromyographic (sEMG) signals generated by the occlusal muscles during clenching. Unlike conventional devices that require hand or foot coordination, this system offers a hands-free and more inclusive approach, particularly targeting users with paraplegia and severe mobility impairments. Myoelectric Signal-Based Control The foundation of this research lies in leveraging sEMG signals from occlusal muscles to generate control commands for the wheelchair. By detecting and processing these myoelectric signals during clenching, the system bypasses traditional motor functions, providing a unique solution for individuals unable to use their limbs effectively. This method demonstrates an innov...

Introduction Laser-assisted turning (LAT) has emerged as a promising technique to enhance the machinability of difficult-to-cut alloys like GH 4169 by utilizing localized thermal softening induced through laser preheating. This study focuses on understanding the influence of laser processing parameters on the thermal field during the preheating process of LAT. By combining finite element (FE) simulation with experimental validation, the research aims to optimize the machining parameters to achieve improved efficiency, reduced tool wear, and superior surface quality. Finite Element Modeling of LAT for GH 4169 A 2D finite element (FE) model is established to simulate the laser-assisted turning of GH 4169, enabling the detailed investigation of thermal field evolution. The model incorporates material properties, boundary conditions, and heat absorption characteristics to predict the influence of laser parameters on the peak and final preheating temperatures. This computational approach...

Introduction The rapid miniaturization and increased functionality of modern electronic devices have significantly raised their power density, creating severe thermal management challenges. Heat dissipation has now become a critical bottleneck, as traditional metallic materials fail to meet the combined demands of high thermal conductivity, lightweight design, and structural flexibility. In this context, graphene oxide (GO)/epoxy resin (EP) composites have emerged as a promising alternative, offering unique advantages in combining polymer versatility with graphene-derived heat transfer efficiency. Thermal Conductivity Enhancement Mechanisms Graphene oxide’s outstanding intrinsic properties, particularly its high in-plane thermal conductivity, make it a powerful candidate for improving the thermal performance of epoxy-based composites. However, the effectiveness of this enhancement depends on several key factors, including GO dispersion quality, interfacial bonding strength, and the con...

Introduction Ground loop interference remains a persistent challenge in analog audio systems, particularly in setups using unbalanced connections. The unwanted hum and noise generated from potential differences in protective earth paths can severely degrade audio quality. To address this issue, a passive Audio Interference Suppressor in Analog Audio Interface (AISAAI) has been developed, offering a robust and cost-effective solution. Integrated into an Analog Audio Interconnection System (AAIS) framework, AISAAI ensures improved sound clarity while maintaining electrical safety. Problem of Ground Loop Interference Unbalanced audio connections are prone to noise due to their direct dependence on shared ground paths. Ground loop interference occurs when multiple devices connected to a protective earth create voltage differences that induce hum into the audio signal. This phenomenon is especially problematic in professional and consumer audio environments where equipment interconnectivity...

Introduction Arizona’s ambitious commitment to reducing emissions by 50–52% by 2030 and reaching net-zero emissions by 2050 demands transformative changes to its electricity infrastructure. Achieving a carbon-neutral grid requires comprehensive planning, integrating renewable energy sources and energy storage systems to replace conventional utility-scale generation. This study employs a MATLAB-based model using hourly electricity load and solar insolation data to evaluate the optimal configuration of solar PV systems and energy storage capacity. Unlike conventional studies that focus solely on maximizing solar capture via tilt optimization, this research considers the broader implications of PV tilt and tracking configuration on land use, storage requirements, and total system costs. Methodology for Solar PV Assessment The research methodology relies on high-resolution, hourly solar insolation data and electricity demand profiles to model the performance of various PV configurations....

Introduction The Global Particle Physics Excellence Awards proudly celebrates the Best Keynote Speaker recognition, an honor dedicated to researchers, innovators, and visionaries who inspire through impactful keynote sessions. This award acknowledges not only contributions to particle physics but also the ability to bridge science, technology, and discovery, creating a strong foundation for global scientific progress. Celebrating Scientific Communication Science thrives when complex concepts are communicated with clarity and passion. The Best Keynote Speaker award emphasizes the importance of effective communication in particle physics, where researchers have the responsibility to make groundbreaking ideas accessible to both scientific peers and the wider audience. This recognition highlights the value of delivering impactful talks that resonate across diverse communities. Leadership in Advancing Knowledge Keynote speakers are not just communicators; they are leaders who advance the fr...

Introduction 3D pixel sensors have gained remarkable attention in recent years, particularly in the field of High Energy Physics, where their superior radiation hardness and fast response times make them highly suitable for demanding applications. Their demonstrated resilience up to fluences of 3×10¹⁶ 1 MeV equivalent neutrons per square centimeter has solidified their role in the innermost tracking layers of upgraded ATLAS and CMS detectors at the High-Luminosity Large Hadron Collider. With future vertex detectors demanding precise timing capabilities, 3D sensors continue to emerge as a promising technology. Radiation Hardness of 3D Pixel Sensors One of the most critical properties of 3D pixel sensors is their exceptional radiation hardness. Unlike traditional planar detectors, the 3D architecture allows for reduced charge collection distances and improved tolerance to extreme irradiation levels. This ensures that even after exposure to very high particle fluences, the sensors can mai...