Local Particle Research Articles

Charged particle scattering near the horizon

We study Maxwell theory, in the presence of charged scalar sources, near the black hole horizon in a partial wave basis. We derive the gauge field configuration that solves Maxwell equations in the near-horizon region of a Schwarzschild black hole when sourced by a charge density of a localised charged particle. This is the electromagnetic analog of the gravitational Dray-’t Hooft shockwave near the horizon. We explicitly calculate the S-matrix associated with this shockwave in the first quantised 1 → 1 formalism. We develop a theory for scalar QED near the horizon using which we compute the electromagnetic eikonal S-matrix from elastic 2 → 2 scattering of charged particles exchanging soft photons in the black hole eikonal limit. The resulting ladder resummation agrees perfectly with the result from the first quantised formalism, whereas the field-theoretic formulation allows for a computation of a wider range of amplitudes. As a demonstration, we explicitly compute sub-leading corrections that arise from four-vertices.

Hydrodynamic Insights on Floating Bubbling Fluidized Beds: Dynamic Solutions for Mitigating Gas Maldistribution

This study examined bubbling fluidized beds as an alternative to fixed-bed dry scrubbers on ships for reducing pollutants from marine fuels. It focused on overcoming the challenges of gas maldistribution/slug formation, especially under rough sea conditions. This research departed from traditional methods by introducing mobile internal elements into the bed emulsion phase and investigating their effectiveness in various settings, such as vertical, inclined, and rolling beds. A specialized hexapod-driven bubbling fluidized bed was developed to mimic marine operating conditions and to study the behavior of shipboard fluidized beds. Techniques such as digital image analysis (DIA) and particle image velocimetry (PIV) were used to observe bubble dynamics and granular phases, measuring local void fractions and particle velocities. A key finding is the effectiveness of moving internals in preventing bubble coalescence, which is critical for avoiding wall slugs, at different inclinations. Three types of packing were used as mobile internals: Super Raschig, Pall, and square rings. Super Raschig rings, which are characterized by high porosity, were the most efficient in reducing bubble coalescence, making them a preferred choice for offshore fluidized bed applications. This research contributes to the advancement of fluidized bed technology in marine applications and provides insight for future improvements.

The bosonic skin effect: Boundary condensation in asymmetric transport

We study the incoherent transport of bosonic particles through a one dimensional lattice with different left and right hopping rates, as modelled by the asymmetric simple inclusion process (ASIP). Specifically, we show that as the current passing through this system increases, a transition occurs, which is signified by the appearance of a characteristic zigzag pattern in the stationary density profile near the boundary. In this highly unusual transport phase, the local particle distribution alternates on every site between a thermal distribution and a Bose-condensed state with broken U(1)U(1)-symmetry. Furthermore, we show that the onset of this phase is closely related to the so-called non-Hermitian skin effect and coincides with an exceptional point in the spectrum of density fluctuations. Therefore, this effect establishes a direct connection between quantum transport, non-equilibrium condensation phenomena and non-Hermitian topology, which can be probed in cold-atom experiments or in systems with long-lived photonic, polaritonic and plasmonic excitations.

Viscosity-modulated clustering of heated bidispersed particles in a turbulent gas

Clustering of externally and evenly heated particles is enhanced by the increased viscosity of heated fluid in the vicinity of these clusters – a phenomenon known as viscous capturing (VC). Herein we study, via direct numerical simulations of decaying turbulence, the effect of temperature-driven viscosity on clustering with different particle loading densities. We employ a two-way momentum and energy coupling, and gas viscosity is modelled by a power law to understand the role of the increased drag and particle back-reaction force on the clustering intensity. For the continuum and dispersed phases, Eulerian and Lagrangian point particle schemes have been used, neglecting inter-particle collisions. We found that the enhanced viscosity-driven clustering is a strong function of particle loading density, as the increase in particle number density enables the formation of large uneven clusters before heating, which is the main condition for VC to take effect. Higher number density should result in greater turbulence modulation and negate local temperature-based viscous effects leading to VC. However, due to higher local particle number density in the clusters and interphase heat transfer, increased drag force prevails in such cases and delivers excessive clustering. By sampling conditionally the particle velocity and temperature inside the clusters, it is found that the thermodynamic and kinematic properties of the particles in the clusters are highly correlated, and this correlation increases with the particle loading density. Therefore, based on the particle number density, temperature-based viscosity can enhance considerably the clustering of heated particles and alter the effect of particles on the underlying turbulence.

DEM and DEM-CFD modeling of systems with geometric constrictions using a new particle location based multi-level coarse graining approach

A popular Lagrangian approach for modeling granular systems is the discrete element method (DEM). Currently, the simulation of industrial granular systems often exceeds modern computer capacities. Therefore, the coarse graining (CG) approach bundles multiple particles into grains, which are less computationally demanding due to the reduced number of entities considered. In systems, where the maximum grain size is limited by local geometry constrictions, uniform grain sizes lead to inefficient computations since far from the constrictions larger grain sizes could be reasonably used. Multi-level coarse graining (MCG) addresses this by using multiple grain sizes, which are adapted to the geometric constrictions. In this study, geometrical non-uniform hoppers and a Wurster coater system were modeled using a new MCG approach. Results from literature regarding hopper discharge were matched. For the Wurster coater system MCG outperforms conventional CG by providing a higher resolution of the granular material close to the geometric constriction.

Quantum backflow for a free-particle hermite wavepacket

Abstract Quantum backflow is the unexpected effect that wavepackets consisting of only positive momentum components can apparently move in the negative direction. This is usually described in terms of the backflow constant, which is a dimensionless quantity describing least upper bound on the amount of probability that can flow backwards during a given time interval. Backflow is usually calculated for wavepackets that can be written as a sum of positive momentum plane waves. Here we present a calculation of the backflow constant using the localised free particle hermite wavefunctions where equal weights of positive and negative momentum eigenfunctions occur. The resulting backflow constant is substantially smaller than the accepted value. The reasons for this are discussed and finally we draw conclusions about the calculation of backflow more generally.

Control of segregation by non-uniform aeration in a fluidized bed spray granulator

Controlling and influencing the rate of particle growth in spray granulators is key for consistent product quality and size, while reducing energy consumption and product re-circulation. To this end, we have implemented a new control device to actively change the fluidization topology of fluidized spray granulators and to influence the local particle segregation in the areas affected by the granulation, selectively growing fine particle fractions at will. Simulations using computational fluid dynamics coupled with the discrete element method (CFD-DEM) demonstrate how the different operational modes can be switched in a short period of time, resulting in full local segregation in less than 40 s, without changing the fluidization air or inlet temperature. It is shown how a central spout preferentially drags big particles to the top of the bed, while a side aeration system, where two smaller spouts are opened at the outermost sides of the bed, creates a concentration of fines in the spraying region. This process can be repeated as long as the fluidization velocity of all particle sizes in the bed can be attained and full fluidization is underway. The spout regime could be used to clean the distributor plate of undesired big or overgrown particles, and side aeration to preferentially grow finer particles, while homogeneous aeration should be the default operation mode when no anomalies are detected.

A stochastic lipid structured model for macrophage dynamics in atherosclerotic plaques.

We propose to model certain aspects of the dynamics of a macrophage that moves randomly in a one dimensional space in arterial wall tissue and grows by accumulating localized lipid particles, thus reducing its motility. This phenomenon has been observed in the context of atherosclerotic plaque formation. For this purpose, we use a system of stochastic differential equations satisfied by the position and diffusion coefficient of a Brownian particle whose diffusion coefficient is modified at each visit to the origin and with a dumping coefficient. The novelty of the model, with respect to Bénichou et al. (Phys Rev E 85(2):021137, 2012), Meunier et al. (Acta Appl Math 161:107-126, 2019), is to include offloading of lipids through the dumping term. We find explicit necessary and sufficient conditions for macrophage trapping in the locally enriched region.

Developing a novel mucociliary clearance boundary condition (MCBC) to simulate micro-scale particle transfers inside the respiratory tract system without generating extra computational cells

The respiratory tract system is protected against pathogens and contaminants by the mucociliary clearance phenomenon. Simulating the effects of mucociliary clearance is an important numerical challenge besides the airflow inside the respiratory tract system. The open-source toolbox (OpenFOAM 7) is used to develop a novel method for modeling mucociliary clearance in the vicinity of airflow without extra computational cells. The new method is developed based on three components including inlet-outlet direction, cilia metachronal wave, and main flow core direction, and can be applied to any other respiratory geometries. The capability of the new method is assessed by applying it to the nasal cavity using the Eulerian-Lagrangian approach. The method is applied to the whole nasal surface except the vestibule region to model mucociliary clearance. The results show all deposited particles inside the nasal valve region are transferred alongside the nasal surface toward the main airway region within 12 min. Although mucociliary clearance does not affect the airflow and deposition location of particles due to its slight velocity, its effect on transferring deposited particles is significant. Particle tracking during 5 min inside a single nasal cavity shows 40 % of deposited particles inside the nasal valve are transferred to the main airway by mucociliary clearance. This novel numerical method can lead to the appearance of new insights into the discovery and development of mucosal-based therapies.

Multiple local particle filter for high-dimensional system identification

Nonlinearity and high dimensionality emerge as two primary challenges in the realm of system identification within the context of structural health monitoring (SHM) applications. Particle filter (PF) has been demonstrated efficient for nonlinear identification, but it suffers from the curse of dimensionality and behaves poorly in high-dimensional problems. The idea of state and measurement partitioning has been used in many PF algorithms to simplify high-dimensional identification problems into the identification of several lower-dimensional subgroups, but with very few applications to SHM problems. In this context, by combining multiple particle filters (MPF) with the decay of correlations property, this paper develops a novel multiple local particle filter (MLPF) for high-dimensional identification problems. A whole state vector is partitioned into several state subgroups, each consisting of fewer state components and then estimated by one PF through a novel likelihood including the local state and measurement vectors. The feasibility and efficiency of the proposed method are tested through a benchmark toy example, a case study of a twenty-story Bouc-Wen frame structure under ground motion, and an experimental study of fatigue delamination growth in composites.

Enhancing Sustainability and Efficiency in Offshore Oil and Gas Engineering through the Integration of Chaotic Local Search and Particle Swarm Optimization for Microenergy Systems Optimization

The offshore oil and gas industry is under increasing pressure to reduce carbon emissions while maintaining energy reliability. Offshore oil and gas platforms (OOGPs) face significant challenges in integrating low‐carbon operations with their energy systems. This study introduces an optimized scheduling approach for offshore microintegrated energy system (OMIES) that incorporates a hybrid energy storage system, including a floating power‐to‐gas associated gas storage (FP2G‐AGS) module, to address the intermittency of renewable energy sources. An economic optimization model is formulated, accounting for carbon emissions, operational costs, and the status of gas turbine generator sets. To solve the complex optimization problem, this study develops a hybrid chaotic local search and particle swarm optimization (CLPSO) algorithm. The CLPSO algorithm synergizes the global search ability of PSO with the local refinement of chaotic local search, enhancing the convergence to optimal solutions. Experimental results demonstrate that the proposed CLPSO algorithm effectively achieves optimal solutions within a range of 48.2–51.7. Case studies validate the model’s capability to promote new energy integration, reduce operational costs, and decrease CO2 emissions across various scenarios. This research significantly contributes to achieving low‐carbon operations on OOGPs and promotes the sustainable development of marine resources.

ChirpTracker: A Precise-Location-Aware System for Acoustic Tag Using Single Smartphone

The increasing interest in loss prevention devices using the Internet of Things, has been driven by the convenience, low cost, and low power consumption of these devices. However, the existing technologies cannot achieve a balance between high availability over a wide area with a single smartphone and precise location awareness. In this paper, a novel Precise-Location-Aware method that integrates acoustic technology and pedestrian dead reckoning, ChirpTracker, is proposed which most smartphones support without auxiliary equipment. This system can provide wide coverage (30m) and is suitable for many scenarios such as searching for cars in underground parking or finding items indoors. ChirpTracker can detect the distance between the smartphone and a lost tag in real time using acoustic signals, it can monitor the relative position change of the smartphone based on deep learning based pedestrian dead reckoning (PDR) and update relative positioning of the lost tag though the observation from single base-station in motion. A technology that combines the local least squares method (LSM) and particle filter (PF) improves the convergence and the robustness of ChirpTracker through an identification strategy for a mirror position. This method was validated in experiments conducted in actual environments. The results demonstrate the effectiveness and positioning accuracy of ChirpTracker.

Embedded Feature Selection Approach Using Penalized Logistic Regression for Universal Steganalysis

For universal steganalysis, the Spatial Rich Model (SRM) provides a robust feature set in the form of 106 feature submodels (34671-dimensional) to attack highly secure steganography methods. Nonetheless, the curse of dimensionality emerges as a drawback, prompting researchers to explore feature selection methods to achieve optimal performance for steganalyzers. In previous work, a wrapper feature selection method using global and local best particle swarm optimization (GLBPSO) has been used to select 28 submodels of SRM out of 106 submodels. The 28 submodels contain a total of 9152 features and an ensemble classifier has been used for the classification results. In this study, an embedded feature selection and classification approach using logistic regression (LR) with an elastic net penalty has been proposed and applied to the 9152 features. The proposed approach efficiently selects an informative subset of 9152 features while training the LR classifier. This not only reduces the number of features by a significant 75% but also boosts the classification performance when contrasted with the ensemble classifier. The proposed approach achieves an accuracy of 87.41%, surpassing the current state-of-the-art steganalysis methods based on deep learning by a substantial margin of 3-7%. It also outperforms a recent machine learning-based steganalysis method by 13%.

Integrable Magnetic Fluid Hyperthermia Systems for 3D Magnetic Particle Imaging.

Background: Combining magnetic particle imaging (MPI) and magnetic fluid hyperthermia (MFH) offers the ability to perform localized hyperthermia and magnetic particle imaging-assisted thermometry of hyperthermia treatment. This allows precise regional selective heating inside the body without invasive interventions. In current MPI-MFH platforms, separate systems are used, which require object transfer from one system to another. Here, we present the design, development and evaluation process for integrable MFH platforms, which extends a commercial MPI scanner with the functionality of MFH. Methods: The biggest issue of integrating magnetic fluid hyperthermia platforms into a magnetic particle imaging system is the magnetic coupling of the devices, which induces high voltage in the imaging system, and is harming its components. In this paper, we use a self-compensation approach derived from heuristic algorithms to protect the magnetic particle imaging scanner. The integrable platforms are evaluated regarding electrical and magnetic characteristics, cooling capability, field strength, the magnetic coupling to a replica of the magnetic particle imaging system's main solenoid and particle heating. Results: The MFH platforms generate suitable magnetic fields for the magnetic heating of particles and are compatible with a commercial magnetic particle imaging scanner. In combination with the imaging system, selective heating with a gradient field and steerable heating positioning using the MPI focus fields are possible. Conclusion: The proposed MFH platforms serve as a therapeutic tool to unlock the MFH functionality of a commercial magnetic particle imaging scanner, enabling its use in future preclinical trials of MPI-guided, spatially selective magnetic hyperthermia therapy.

Jetting and droplet formation of particle-loaded fluids

Inkjet printing is an attractive method for patterning and fabricating objects across many areas of industry. There is a growing interest in the printing of inks with high particle-loading, such as inks containing glass frit, ceramic and functional inks. However, the use of these inks is often limited due to uncertainty regarding the impact of their rheology on the printing process. Understanding of the role of complex rheology in the jetting of loaded inks is therefore needed to facilitate the wider application of inkjet printing. Here, we characterize the complex rheology and the jetting of model dispersion inks (containing 10, 15, and 23 vol. % TiO2 nanoparticles) and compared them with those without particles. The jetting of the model fluids was conducted with a commercial inkjet printhead (nozzle diameter 34 μm) and visualized with stroboscopic and ultra-high-speed imaging. For low particle concentrations, droplet formation is generally similar to those of unloaded inks, provided their Ohnesorge number and Weber number are matched, although the filament of the loaded model fluid tends to have earlier break-off, having a shorter length. The jetting reliability decreased with increase in particle-loading until reliable jetting can no longer be achieved, due to local particle–particle interactions in the ink channel and in the filament during the fast extensional thinning process. A jetting map is presented which illustrates the influence of particle-loading on the droplet formation, and indicates that the acceptable range of Ohnesorge number for jetting is reduced as the particle-loading is increased.

Enabling the characterization of the nonlinear electrokinetic properties of particles using low voltage.

Insulator-based electrokinetically driven microfluidic devices stimulated with direct current (DC) voltages are an attractive solution for particle separation, concentration, or isolation. However, to design successful particle manipulation protocols, it is mandatory to know the mobilities of electroosmosis, and linear and nonlinear electrophoresis of the microchannel/liquid/particle system. Several techniques exist to characterize the mobilities of electroosmosis and linear electrophoresis. However, only one method to characterize the mobility of nonlinear electrophoresis has been thoroughly assessed, which generally requires DC voltages larger than 1000 V and measuring particle velocity in a straight microchannel. Under such conditions, Joule heating, electrolysis, and the DC power source cost become a concern. Also, measuring particle velocity at high voltages is noisy, limiting characterization quality. Here we present a protocol-tested on 2 μm polystyrene particles-for characterizing the mobility of nonlinear electrophoresis of the liquid/particle system using a DC voltage of only 30 V and visual inspection of particle dynamics in a microchannel featuring insulating obstacles. Multiphysics numerical modelling was used to guide microchannel design and to correlate particle location during an experiment with electric field intensity. The method was validated against the conventional characterization protocol, exhibiting excellent agreement while significantly reducing measurement noise and experimental complexity.

Conductive filament distribution in nano-scale electrochemical metallization cells.

We report a combined experimental and theoretical study of the spatial distributions and sizes of conductive filaments in nano-scale electrochemical metallization (ECM) cells. Each cell comprises a silver nanocube as active electrode, a titanium dioxide (TiO2) or aluminum oxide (Al2O3) layer as dielectric, and a highly-doped silicon substrate as passive counter electrode. Following electroforming of the ECM cell and subsequent mechanical delamination of the silver nanocubes, current maps at previous particle locations reveal an intriguing metal distribution in the TiO2, with preferential accumulation close to the original locations of the nanocube edges. We assign this behavior to electric field enhancements close to the cube edge positions. In contrast, filaments in Al2O3 layers show a comparatively homogenous distribution, which may be assigned to its lower dielectric permittivity. By increasing the oxide thickness, the total area of conductive spots in the current maps increases monotonically for both materials. Kinetic Monte-Carlo simulations of ion migration dynamics in TiO2 confirm the experimental observations, describing both the preferred locations and oxide thickness-dependent metal loadings associated with filament formation. Overall, our findings are highly valuable for the design of future electrochemical metallization cells, especially in the sub-100 nm regime, where optimal filament control is of major importance for achieving lowest device-to-device variability.

Investigation of the Relationship Between the Structural Properties and Air, Water Drop and Particle Permeability of Different Masks Available in the Market

This study was performed on the masks which started to have vital importance after the Covid-19 which were first seen in China at the end of 2019 and spread all over the world in a short time and became a global epidemic. By examining the structural and morphological properties (number of layers, fabric properties used in different layers, average fiber diameter, fiber distribution, average porosity diameter, etc.) of different masks procured from local producers, air permeability, water drop and particle permeability were investigated. Structural and morphological properties of different layers of masks were observed through SEM analysis. The air permeability analysis of the masks was performed at 100 pascals pressure, in an area of 5 cm2 in 4 repetitions using Textest-Fx 3300 Air Permeability Device. The water drop permeability analysis was carried out with 0.3 µM NaCl solution under standard atmospheric conditions in a non-pressurized environment. A crocmeter was used for particle permeability analysis. And it was tested whether the fine particulate dust passed to the back of the mask. It has been determined that the air permeability, water drop and particle permeability behavior of the masks with different structural and morphological properties are very different.

Biochar modifies soil physical properties mostly through changes in soil structure rather than through its internal porosity

AbstractBesides its carbon sequestration potential, biochar application generally improves soil physical properties, but the magnitude of its impact and the underlying mechanisms remain debated and depend on soil type, biochar application rate, and age. The objective was therefore to determine the effect of biochar application rate and age on physical properties of agricultural soils in a temperate climate. On a silt loam and a sandy loam soils, we compared the physical properties of fresh biochar (1% and 2% w/w) or century‐old biochar (0.5%–1% w/w; 19th‐century kiln sites)‐enriched soil samples with biochar‐free soil samples. Biochar pore network characteristics were determined using helium pycnometry, mercury intrusion porosimetry, scanning electron microscopy observation, and electron dispersive X‐ray spectrometry, whereas location of biochar particles within soil structure was analyzed using optical microscopy observations. Fresh biochar application decreased bulk density by 16.8% and increased saturated water content by 16.0% and macroporosity by 78.8%. These effects were attributed to soil structure improvement rather than to biochar porosity. Soil type and biochar application rate had a limited impact. In the long‐term, biochar effects were mostly nonsignificant, which might result from its fairly low content in kiln sites and from the clogging of its internal porosity by clay particles. Biochar was thus able to improve some soil physical properties in the short‐term, but these effects could no longer be detected in the very long‐term. Further investigating the time rate of change in soil physical properties over several decades following biochar additions to soil would therefore seem particularly relevant.

Enhancing Durability of Polymer Electrolyte Membrane Water Electrolyzer through Incorporation of Gas Recombination Catalyst in Membrane

Hydrogen will become a critical component of the future energy landscape driven primarily by the growing use of renewable energy sources. Polymer electrolyte membrane water electrolyzer (PEMWE) is a superior technology to facilitate hydrogen production from renewable electricity. However, durability remains a significant challenge for the widespread commercialization of electrolyzers.1 Cross-over of H2 from cathode to anode could lead to explosive mixtures in the anode causing safety concerns during operation. Hydrogen crossover also impacts the durability of the anode catalyst.2 Hydrogen permeation from the cathode to the anode through the membrane reduces the anodic Ir catalyst to a low valence state leading to increased dissolution of the Ir catalyst at a high cell voltage. Utilizing thin membranes (~50µm) can improve the electrolyzer system’s efficiency but also increase the hydrogen permeation, particularly at high pressures.In this study, we present a methodology to incorporate platinum as a gas recombination catalyst (GRC) layer into commercial membranes, significantly reducing hydrogen permeation rates and mitigating anode catalyst degradation. Membranes with GRC can mitigate the degradation of PEMWE, leading to more efficient and durable PEM electrolysis systems for hydrogen production. The methodology developed enables higher control of the GRC layer properties (Pt particle size and location in the membrane). Ex-situ measurement of hydrogen permeation, shown in Figure 1, indicates a significant reduction in the permeation rate for GRC incorporated NR 212. This study presents a systematic electrochemical evaluation of anode degradation in PEMWE with and without GRC in the membrane using accelerated stress tests. The durability of the GRC during long-term operation is also presented. Acknowledgment This research is supported by the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office through the Hydrogen from Next-generation Electrolyzers of Water (H2NEW) consortium.