Global Particle Physics Excellence Awards

Introduction The Excellence in Research Award stands as a global tribute to the brilliance, perseverance, and vision of scientists and researchers dedicated to advancing human knowledge. Organized by ScienceFather under the Global Particle Physics Excellence Awards , this honor recognizes individuals whose groundbreaking research has made a transformative impact in their disciplines. The award highlights not just scientific achievement but the spirit of innovation and collaboration that drives progress across academia, industry, and society. Advancing Global Scientific Knowledge Scientific discovery is the cornerstone of human progress. The Excellence in Research Award celebrates those who push the limits of understanding through novel methodologies and innovative experiments. By acknowledging researchers who contribute to expanding global knowledge, the award reinforces the importance of continuous exploration and scientific curiosity that drives technological and societal evolutio...

Introduction Understanding charge injection phenomena at the metal/epoxy interface is fundamental for optimizing the performance and safety of high-voltage electrical equipment . The behavior of charge transfer, injection barriers, and interfacial electronic structures significantly impacts the insulation reliability and operational lifespan of systems such as high-voltage direct current (HVDC) gas-insulated switchgear (GIS). By employing first-principles calculations , this study provides valuable insights into the charge injection mechanisms influenced by molecular design and curing agent chemistry , which are crucial for developing advanced insulating materials with superior dielectric stability . Significance of Charge Injection in HVDC Systems In HVDC GIS systems, charge accumulation at interfaces can lead to electrical breakdowns, reducing system efficiency and safety. Investigating the microscopic mechanisms of charge injection between metal electrodes and polymeric insulato...

Introduction The development of high-performance supercapacitors demands electrode materials with optimized electronic configurations and defect chemistries. Transition metal oxides , particularly cobalt oxide (Co₃O₄), have garnered substantial attention due to their high theoretical capacitance, diverse redox states , and excellent electrochemical reversibility. However, their practical application is limited by poor conductivity and structural instability during charge–discharge cycles. This study introduces a rational approach to designing rare earth (RE)-assisted cobalt oxide gels via a controlled sol–gel synthesis method . The incorporation of neodymium (Nd) and gadolinium (Gd), individually and synergistically, into the Co₃O₄ matrix has been shown to tailor the material’s microstructure, defect density, and electrochemical behavior, thereby unlocking new pathways for developing efficient and durable energy storage systems. Structural Engineering of Rare Earth-Doped Co₃O₄ Gels S...

Introduction In modern microgrids, reliable and adaptive protection schemes are essential to ensure system stability during internal faults and dynamic operating conditions. Traditional inverse-time overcurrent (ITOC) protection often struggles to maintain coordination between protection levels when switching between grid-connected and islanded modes, resulting in delayed fault clearance and reduced reliability. To overcome these limitations, an improved inverse-time overcurrent protection scheme based on a composite parameter protection factor is proposed. This method integrates voltage and current phase relationships with voltage sag severity to enhance responsiveness and selectivity. By embedding both phase-difference and voltage-sag acceleration factors, the scheme ensures rapid and coordinated protection operation, improving overall fault management and stability in complex microgrid environments. Problem Statement in Traditional ITOC Schemes Traditional ITOC protection schemes...

Introduction The proposed semi-analytic harmonic modeling method represents a transformative advancement in the study of complex magnetic field systems. By integrating both analytical and numerical approaches, this method bridges the gap between precision and computational efficiency, two essential yet often conflicting aspects of magnetic field analysis. Traditional techniques such as the equivalent charge method and finite element method have shown limitations in handling material non-uniformity and high-order harmonic effects. The newly introduced model resolves these constraints through optimized surface and body charge distribution and variable permeability treatment. This approach particularly enhances the modeling of advanced magnetic configurations such as Halbach arrays, where field uniformity and control are critical. The semi-analytic harmonic modeling method thus establishes a new benchmark for precision-driven, efficient magnetic field simulation. Semi-Analytic Harmonic M...

Introduction The concept of shared space has emerged as a sustainable urban design approach aimed at improving the safety and health of vulnerable road users (VRUs) by promoting walking and cycling. By minimizing traditional traffic segregation, shared spaces encourage human interaction and mutual awareness among pedestrians, cyclists, and e-bike riders. However, as the complexity of these interactions increases, concerns regarding the frequency and severity of conflicts also arise. This research investigates the microscopic behavioral patterns and psychological responses of road users in shared spaces to better understand how individual decisions and perceptions influence overall safety and comfort levels. Research Objectives and Methodology The study focuses on examining the behavioral and psychological mechanisms underlying pedestrian–e-bike and pedestrian–cyclist interactions in non-motorized shared spaces. A total of 334 interactions were observed and analyzed using the Dutch Ob...

  Introduction The Outstanding Scientist Award 2025 stands as a symbol of global recognition for researchers whose exceptional contributions have shaped modern science and technology. Organized under the Global Particle Physics Excellence Awards , this accolade honors scientific pioneers who embody innovation, curiosity, and impact. It serves as a platform to celebrate excellence across diverse disciplines such as physics , chemistry , biology , and engineering , inspiring the next generation of scientific leaders to continue the pursuit of knowledge and progress for the betterment of society. Innovation in Scientific Research Innovation lies at the heart of scientific advancement, driving discoveries that transform human life and redefine our understanding of the universe. The Outstanding Scientist Award 2025 highlights researchers who have developed groundbreaking methods, tools, or technologies that revolutionize their fields. By celebrating innovative minds, the award unde...

  Introduction The development of advanced biomedical materials demands surfaces that offer superior mechanical stability and biocompatibility. In this context, Ti-Al alloys have gained considerable attention due to their excellent corrosion resistance and mechanical properties . This study introduces a novel approach for enhancing the surface characteristics of Ti-Al alloys through aluminum deposition using Electrical Discharge Machining (EDM). By creating a compositional gradient and forming metallurgically bonded intermetallic zones , the research aims to provide a robust foundation for hydroxyapatite (HA) coating adhesion . The comprehensive analysis of the formed layers, including their structural, chemical, and mechanical properties, highlights the potential of EDM-assisted surface modification for biomedical applications. Methodology of Aluminum Deposition via EDM The aluminum deposition process was conducted using EDM under carefully controlled parameters to ensure uni...

Introduction The evaluation of compaction quality in earthworks and pavements traditionally relies on density -based acceptance methods derived from laboratory Proctor tests . While effective, these methods are time-intensive, costly, and spatially limited. The lightweight dynamic cone penetrometer (LDCP) offers a rapid, on-site alternative capable of producing key indices such as 𝑞𝑑0 and 𝑞𝑑1. However, the reliability of LDCP data often depends on site-specific calibrations, restricting its general application. To overcome these challenges, this research introduces a supervised machine learning framework designed to predict LDCP indices directly from soil descriptors, thereby optimizing the process of compaction quality control and enhancing operational efficiency in geotechnical field applications. Methodological Framework The study employed a supervised machine learning framework integrating multiple predictive models to estimate the LDCP indices 𝑞𝑑0, 𝑞𝑑1, and 𝑍𝑐. The data...