Global Particle Physics Excellence Awards

  Physics-informed Gaussian process probabilistic modeling with multi-source data for prognostics of degradation processes The integration of physics-based and data-driven methods in prognostics has become increasingly important in understanding the underlying degradation process using available knowledge.  In this paper, we propose a physics-informed Gaussian process modeling method with multi-source data (PIGP-MD) that improves the predictive power of standard Gaussian process model by incorporating the prior knowledge from both physical models and historical data, and the current knowledge from limited observation data.  We first propose a PIGP modeling method that incorporates the prior knowledge solely from physical models. In PIGP, a standard GP directly trained with current observation data is used to truncate the random realizations generated from physical models within the confidence bounds of the GP prediction.  The truncated random realizations are used to...

  Biomass gasification modeling based on physics-informed neural network with constrained particle swarm optimization Significant interest has emerged in using machine learning (ML) methods to predict biomass gasification performance. However, insufficient experimental data often hinders ML models' ability to accurately characterize the gasification process.  Therefore, this study proposed a novel hard-constrained physics-informed neural network (HC-PINN) to predict biomass gasification syngas components. This method employs a hard-constrained learning approach and a constrained particle swarm optimization algorithm to ensure that the constructed model fully obeys the given monotonicity constraints and aligns with experimental data.  A comprehensive dataset collected from the existing articles was utilized to model the biomass gasification process by the HC-PINN and six advanced ML approaches.  The results show that the HC-PINN model demonstrates impressive performan...

 Best Researcher Award The Best Researcher Award is a prestigious recognition that celebrates individuals who push the boundaries of science, technology, and discovery. It honors those who make groundbreaking advancements that shape the future of research and inspire the next generation of scholars. Eligibility Criteria The Best Researcher Award is open to all researchers and scientists , regardless of their career stage or research domain. ✔ No Age Limit – Open to researchers at all levels, from emerging scholars to senior scientists. ✔ Open to All Disciplines – Whether you specialize in medicine, artificial intelligence, engineering, physics, social sciences, environmental studies, or any other field , you are eligible. ✔ Robust Research Portfolio – Applicants must have a strong track record of impactful research, publications, and discoveries. ✔ Commitment to Knowledge Advancement – This award recognizes individuals who have demonstrated sustained contributions to their f...

  Quantum-classical mechanics as an alternative to quantum mechanics in molecular and chemical physics In quantum mechanics, the theory of quantum transitions is grounded on the convergence of a series of time-dependent perturbation theory. In nuclear and atomic physics, this series converges because the dynamics of quantum transitions (quantum jumps) are absent by definition.  In molecular and chemical physics, on the contrary, the dynamics of “quantum” transitions, being determined by the joint motion of a light electron (or electrons) and very heavy nuclei, are present by definition, and the series of time-dependent perturbation theory becomes singular. An exception is the dynamic problem for stationary states in the Born-Oppenheimer adiabatic approximation, when the electronic subsystem turns out to be “off” from the general dynamic process and therefore is not dynamically full-fledged: it only forms an electric potential in which the nuclei oscillate. Removing the aforeme...

  Numerical investigation and optimization of vertical pneumatic separation of film-like particles in lithium iron phosphate battery recycling Battery recycling is crucial due to its environmental and economic benefits, with efficient separation of the crushed battery mixture forming the basis of the process. However, numerical studies on this process remain limited primarily due to the highly non-spherical shapes of the particles involved.  Spherical particles are commonly used in limited numerical investigations with compromised accuracy and reliability. In this study, the separation of crushed battery mixture by vertical pneumatic separator is simulated using the coupled method of computational fluid dynamics (CFD) and discrete element method (DEM).  The non-spherical particles in the crushed battery mixture is resembled by cylindrical film-like particles, and the Hölzer and Sommerfeld drag coefficient is applied to enhance the accuracy of the drag force calculation. A...

  Blue Ghost Mission 1 réussit son alunissage : « Nous sommes sur la Lune ! » La mission Blue Ghost 1, menée par Firefly Aerospace en collaboration avec la NASA, a réussi son alunissage le 2 mars 2025 à 3h34 EST (8h34 UTC). Le module s'est posé près de Mons Latreille, au sein du bassin Mare Crisium, situé dans le quadrant nord-est de la face visible de la Lune. Cette mission marque une étape significative dans l'exploration spatiale commerciale, Firefly Aerospace devenant la première entreprise privée à réussir un atterrissage en douceur sur la Lune. Houston Chronicle Blue Ghost 1 a été lancé le 15 janvier 2025 depuis le Centre spatial Kennedy en Floride, à bord d'une fusée Falcon 9 de SpaceX. Le module transporte dix instruments scientifiques et technologiques, totalisant 94 kg, destinés à étudier divers aspects de l'environnement lunaire. Parmi eux : Regolith Adherence Characterization (RAC) : détermine comment la poussière lunaire adhère à différentes ...

  A physics-informed clustering approach for ultrasonics-based nondestructive evaluation We propose a physics-informed clustering (PIC) algorithm tailored for ultrasonic non-destructive evaluation. Ultrasonic pulse-echo testing is used to measure the wave speed and wave amplitude decay of additively manufactured AlSi10Mg samples with programmatically induced pores and varying total volumetric porosities.  The standard k-means clustering algorithm is coupled with the Independent Scattering Approximation (ISA) model to group together samples of similar porosity based on their ultrasonic response.  The performance of the proposed PIC algorithm across varying seeds and numbers of clusters is compared to that of the standard k-means algorithm with random and k-means++ initializations. We demonstrate that the proposed PIC algorithm yields a more favourable clustering in terms of Pearson correlation coefficient and mean squared error given the ground-truth porosity labels. ...