Particle Interactions Research Articles

Tuning the rheological properties of paraffin-wax ceramic feedstocks for deposition with thermoplastic 3D printing

Droplet deposition with material-jetting methods such as thermoplastic 3D printing (T3DP) depends greatly on the rheological properties of the feedstocks. This study investigated the effect of particle interactions and the degree of weak flocculation on the shear thinning behaviour, the yield stress and the storage/loss moduli of paraffin-wax-based feedstocks containing 40 vol% of zirconia (3Y-TZP) micron-sized powder. Steric stabilization of the feedstocks was provided by varying the ratios of the surfactants with different chain lengths, i.e., stearic acid (2.4 nm) and Solsperse 3000® (10 nm), which in turn affected the dynamics of the droplet formation and the quality of the layers when jetting non-Newtonian, thermoplastic ceramic feedstocks. The results of the study extend the guidelines for the processing of printable feedstocks used in T3DP additive manufacturing.

Simulation of storage of cold energy considering unsteady conduction mechanism in mathematical model

To enhance system productivity, fins were incorporated into the container, and PCM (phase change material) infused with alumina nanoparticles was introduced. Mathematical modeling was employed to evaluate the current problem, with a specific focus on utilizing water as the PCM for achieving the fastest solidification process. The integration of fins, PCM, and nano-powders introduces a novel dimension to the research, providing unique insights into enhancing solidification processes. The surrounding cold walls of the container play a crucial role in solidification, primarily through conduction. The low speed of H2O allows its neglect in simulation. The developed mathematical model for this work comprises two equations. While considering larger powder sizes improves particle interaction, the negative impact of sedimentation diminishes conductivity. The addition of nanoparticles results in a 41.34 % enhancement in the solidification rate. Furthermore, altering the powder diameter from thirty to 40 nm reduces the completion time about 19.98 %, whereas an increase from 40 to 50 nm elevates it by about 49.37 %.

The effect of shear-induced segregation on bidisperse suspension settling

Shear is a common phenomenon in practical mineral processes, particularly in pipeline transportation. When applied to realistic polydisperse systems consisting of particles of different sizes, shear can lead to distinct interactions of each size component with the carrier fluid, resulting in segregation between sizes. This paper focuses on the effect of size segregation induced by shear on the settling process of suspension flows containing different-sized spherical particles. In this regard, the bidisperse system is considered as the simplest example of polydisperse flows, ensuring the investigation retains the essential features of the system of interest without added complexity. The Volume Penalization Immersed Boundary Method, as a resolved Eulerian–Lagrangian CFD-DEM approach, is employed to gain detailed information on individual particles. A simple cross shear is generated by the moving side walls, and its effect is initially evaluated on two simulation cases containing single spherical particles of different sizes. The results from the single particle simulation cases reveal a higher acceleration of the larger particle towards the centreline due to the higher lateral force proportional to its size. The resolved approach is then used for the bidisperse multiparticle systems with diameter ratios of l=2 and l=5, both subjected to a similar sheared field. In the suspension with l=2, the scalar dispersion function, which measures the degree of migration of each size component between the side walls, indicates segregation by size as the shear rate increases. This is evident in the motion of large particles towards the centre and the accumulation of smaller particles near the walls, which arises from higher proportional force on the larger particles observed in the single particle simulation cases. Although the increase in the diameter ratio to l=5 does not significantly change the migration behaviour of large particles, it provides a more uniform distribution of smaller ones. In this case, the small particles find it more easily to fit into the gaps between the large particles for l=5. Overall, this accumulation of each size component at specific regions in the sheared domain affects the local interaction of settling particles with the fluid flow, resulting in an increase in the settling rate of large particles up to 40% in the considered bidisperse cases. This highlights the impact of shear on the interaction of spherical particles in a multiple sized system, specifically in the practical sheared applications including mineral slurries transportation.

Dynamics of electron capture in positron‐hydrogen scattering under dense semi‐classical plasmas

AbstractThe scattering dynamics of electron capture in ‐H(1 s) scattering under dense semi‐classical plasma (DSCP) environments has been investigated theoretically. Coupled multi‐channel two‐body Lippmann‐Schwinger equations have been solved by retaining +H(1 s) and p + Ps(1 s) channels to calculate the cross sections (CS) of the electron capture process at intermediate and high incident energies. The effective interaction of the plasma charged particles is modelled by a pseudopotential which is a function of two parameters, namely the plasma screening strength and the de Broglie wavelength. A detailed study is made to explore the changes in the CSs of the above‐mentioned process with respect to the variation in the plasma screening strength and de Broglie wavelength. Significant changes are found to take place, when the screening strength and the de Broglie wavelength are varied. Specifically, the sharp minimum in the differential CS moves toward the forward direction with increasing de Broglie wavelength at a given screening strength.

Thermodynamic signatures and phase transitions in high-energy Au–Au collision

In this study, we systematically investigate the dynamics of various hadrons namely π +, π −, K +, K −, p, p¯ , Λ, Λ¯ , Ξ− and Ξ¯+ produced in central Au–Au collisions. We analyze data of AGS and RHIC, which span a broad range of collision energies, ranging from sNN = 1.9 to 200 GeV. To analyze the transverse momentum (p T ) and transverse mass (m T ) distributions, we employ a two-component standard distribution function, achieving a very good representation of the experimental data across these energy regimes. We extract key thermodynamic parameters, including the effective temperature T, the mean transverse momentum 〈p T 〉, and the initial temperature T i , and analyze their dependence on the values of collision energy and particle mass. Our findings reveal a distinct transition behaviour around sNN=19.6GeV . Below sNN=19.6GeV , the values of T, 〈p T 〉, and T i increase monotonically for all hadrons due to higher energy transfer into the system. Above this energy threshold, these extracted parameters plateau, suggesting that the additional energy is utilized as latent heat for phase transition rather than increasing the system’s temperature. These observations delineate two distinct regions: a hadron-dominated region at lower energies and a parton-dominated region at higher energies, each potentially indicative of different phases of matter, with the latter possibly signalling the onset of a quark–gluon plasma. The study thus provides critical insights into the complex interplay of thermodynamics, phase transitions, and particle interactions in high-energy Au–Au collisions.

Impact of particle arrangement and model dimensions on DEM modeling of high-speed railway ballasted tracks in 2D and 3D

Modelling railway projects has a main challenge in the discrete element method (DEM). The granular material of the embankment consists of millions of fine angular particles which are difficult to model due to the long computational time. The long computational time also prevents the modeling of the higher number of loading cycles. As a result, researchers prefer to simulate the project in 2D to accelerate the simulation. While 2D simulations present a seemingly simple option for modeling railways, they tend to oversimplify the intricacies of particle interactions and the distribution of stress. Nonetheless, the extent to which these simplifications affect the authenticity of the simulations has remained ambiguous. In this study, the periodic cell replication method is used to build extensive long railway tracks significantly faster than conventional methods. Then, this DEM model is calibrated against the measurement results of a physical full-scale ballasted track. The model is then used to simulate several railway projects with different initial particle arrangements and model dimensions in both 2D and 3D. The results show that the 2D models are more dependant on the initial particle arrangement which shows different behavior for the same model. In addition, 2D simulations are incapable of reproducing the principal stress rotation in granular layers due to the moving load of the train wheel. As a result, 3D DEM simulations using the periodic cell replication method is suggested for studying the railway tracks.

A collision operator for describing dissipation in noncanonical phase space

The phase space of a noncanonical Hamiltonian system is partially inaccessible due to dynamical constraints (Casimir invariants) arising from the kernel of the Poisson tensor. When an ensemble of noncanonical Hamiltonian systems is allowed to interact, dissipative processes eventually break the phase space constraints, resulting in a thermodynamic equilibrium described by a Maxwell–Boltzmann distribution. However, the time scale required to reach Maxwell–Boltzmann statistics is often much longer than the time scale over which a given system achieves a state of thermal equilibrium. Examples include diffusion in rigid mechanical systems, as well as collisionless relaxation in magnetized plasmas and stellar systems, where the interval between binary Coulomb or gravitational collisions can be longer than the time scale over which stable structures are self-organized. Here, we focus on self-organizing phenomena over spacetime scales such that particle interactions respect the noncanonical Hamiltonian structure, but yet act to create a state of thermodynamic equilibrium. We derive a collision operator for general noncanonical Hamiltonian systems, applicable to fast, localized interactions. This collision operator depends on the interaction exchanged by colliding particles and on the Poisson tensor encoding the noncanonical phase space structure, is consistent with entropy growth and conservation of particle number and energy, preserves the interior Casimir invariants, reduces to the Landau collision operator in the limit of grazing binary Coulomb collisions in canonical phase space, and exhibits a metriplectic structure. We further show how thermodynamic equilibria depart from Maxwell–Boltzmann statistics due to the noncanonical phase space structure, and how self-organization and collisionless relaxation in magnetized plasmas and stellar systems can be described through the derived collision operator.

Self-reverting vortices in chiral active matter

There is currently a strong interest in the collective behavior of chiral active particles that can propel and rotate themselves. In the presence of alignment interactions for many chiral particles, chiral self-propulsion can induce vortex patterns in the velocity fields. However, these emerging patterns are non-permanent, and do not induce global vorticity. Here we combine theoretical arguments and computer simulations to predict a so-far unknown class of collective behavior. We show that, for chiral active particles, vortices with significant dynamical coherence emerge spontaneously. They originate from the interplay between attraction interactions and chirality in the absence of alignment interactions. Depending on parameters, the vortices can either feature a constant vorticity or a vorticity that oscillates periodically in time, resulting in self-reverting vortices. Our results may guide future experiments to realize customized collective phenomena such as spontaneously rotating gears and patterns with a self-reverting order.

Unified framework for the separation property in binary phase-segregation processes with singular entropy densities

Abstract This paper investigates the separation property in binary phase-segregation processes modelled by Cahn-Hilliard type equations with constant mobility, singular entropy densities and different particle interactions. Under general assumptions on the entropy potential, we prove the strict separation property in both two and three-space dimensions. Namely, in 2D, we notably extend the minimal assumptions on the potential adopted so far in the literature, by only requiring a mild growth condition of its first derivative near the singular points $\pm 1$ , without any pointwise additional assumption on its second derivative. For all cases, we provide a compact proof using De Giorgi’s iterations. In 3D, we also extend the validity of the asymptotic strict separation property to the case of fractional Cahn-Hilliard equation, as well as show the validity of the separation when the initial datum is close to an ‘energy minimizer’. Our framework offers insights into statistical factors like particle interactions, entropy choices and correlations governing separation, with broad applicability.

Study of gamma, neutron, and proton interaction parameters of some immunotherapy drugs using EpiXs, NGCal, and PSTAR software

Abstract In proton therapy, the protons are used to destroy the cancer cells efficiently at the Bragg peak without much damage to normal cells. The protons can also produce neutrons, protons, and high-energy gamma rays through nuclear reactions with cancerous and healthy tissues as well as with beamline components. The effective observed dose in the therapy is enhanced due to the interaction of nuclear particles with cancerous tissues. Such nuclear particles can have several effects on drugs used in immunotherapy, such as immunotherapy in combination with proton therapy, which has been used to treat cancer. In the present investigations, the gamma, neutron, and protons interaction parameters of some immunotherapy drugs, such as dostarlimab, atezolizumab, ipilimumab, nivolumab, and pembrolizumab, are determined by using EpiXs, NGCal, and PSTAR software. It is found that the EBF and EABF for all selected immunotherapy drugs increase with increasing penetration depth, peaking at 100 keV. The peaking is more symmetric at a higher penetration depth of 40 mfp than at a lower one of 1 mfp. At lower energies of gamma photons, the EBF values increase exponentially, and at higher energies, they increase linearly with increasing penetration depth for all selected drugs. Mass attenuation factors are slightly higher for thermal neutrons than for fast neutrons for selected immunotherapeutic drugs, indicating that thermal neutrons more actively participate in these drugs than fast neutrons. The mass attenuation factor for both fast and thermal neutrons increases with increasing weight percentages of hydrogen and is found to be higher for thermal neutrons. This is the first study in the literature to investigate the radiation interaction parameters for immunotherapy drugs, and it is helpful in radiation therapy and dosimetry.

Polyoxometalate coupled polymers induced molybdenum phosphide with large surface area for efficient hydrogen evolution

Developing highly active hydrogen evolution reaction (HER) electrocatalysts possesses great significance for the green renewable energy conversion and storage. Here, through the electrostatic attraction between polyoxometalate (PMo12) and ammonium polyphosphate (APP) and the coordination with polyallylamine hydrochloride (PAH), the precursor was constructed, and then nitrogen-doped graphite carbon layer-coated MoP active particles (MoP@NC) were successfully prepared by high temperature carbonization. For HER, the overpotential of η10 for MoP@NC is 119 and 126 mV in acidic and alkaline electrolyte. Furthermore, in alkaline solution, when the current density reaches a certain degree (≥110 mA cm−2), the hydrogen production activity of the catalysts are the same as that of the industrial Pt/C catalysts, or even have a slight advantage. The synergistic interaction of active particles (MoP) and graphitic carbon layers and high specific surface area ensure the excellent activity of HER. N-doped porous carbon layers also protect MoP@NC working for 24 h. Moreover, the catalysts prepared in the same experimental environment with ammonium molybdate as metal source also showed good HER performance in acidic and alkaline environments. This study opens a general way to develop earth-rich Mo-based phosphide electrocatalysts with high activity for hydrolysis applications.

Elastocapillary interaction for particles trapped at the isotropic-nematic liquid crystal interface.

We present numerical simulations on pairwise interactions between particles trapped at an isotropic-nematic liquid crystal (Iso-N) interface. The particles are subject to elastocapillary interactions arising from interfacial deformations and elastic distortions of the nematic phase. We use a recent model based on a phase-field approach [see Qiu etal., Phys. Rev. E 103, 022706 (2021)2470-004510.1103/PhysRevE.103.022706] to take into account the coupling between elastic and capillary phenomena. The pair potential is computed in a two-dimensional geometry for a range of particle separations and two anchoring configurations. The first configuration leads to the presence of an anchoring conflict at the three-phase contact line, whereas such a conflict does not exist for the second one. In the first case, the results show that significant interfacial deformations and downward particle displacements occur, resulting in sizable attractive capillary interactions able to overcome repulsive elastic forces at intermediate separations. The pair potential exhibits an equilibrium distance since elastic repulsions prevail at short range and prevent the clustering of particles. However, in the absence of any anchoring conflict, the interfacial deformations are very small and the capillary forces have a negligible contribution to the pair potential, which is fully repulsive and overwhelmed by elastic forces. These results suggest that the self-assembly properties of particles floating at Iso-N interfaces might be controlled by tuning anchoring conflicts.

Apatite–Wollastonite (AW) glass ceramic doped with B2O3: Synthesis, structure, SEM, hardness, XRD, and neutron/charged particle attenuation properties

In the study, the influence of doping apatite-wollastonite (AW) glass-ceramics (GCs) with B2O3 on the structural, physical, microstructural, and light and heavy particle interaction properties is presented. Using the solid-state reaction and the cold isostatic press method, pristine AW, 10 wt% (AW-B10), and 20 wt% (AW-B20) B2O3-doped AW GCs were prepared. The prepared GCs were subject to structural, chemical compositional, and surface morphological investigation through standard experimental processes. Furthermore, the neutron (fast and thermal) and charged radiation (electron, proton, alpha, and carbon ion) interactional parameters of the GCs were obtained through standard theoretical models and software. The density of AW (2.91 gcm−3) increases to about 2.957 and 2.986 gcm−3 as B2O3 increases to 10 and 20 wt%, respectively. The presence of boron oxide supported the wollastonite phase to remain glass and suppressed crystallisation in the AW GCs. Doping AW with B2O3 improved the interaction probabilities of the GCs with fast and thermal neutrons, electrons, protons, alpha particles, and carbon ions. B-rich AW is thus potentially useful as a target material in human tissues for boron neutron capture therapy for the management of cancer and tumours, isolating or shielding specific tissues in ion beam therapy processes, and other techniques that require the exposure of human tissues to irradiation.

Reduced Variance Random Batch Methods for Nonlocal PDEs

Random Batch Methods (RBM) for mean-field interacting particle systems enable the reduction of the quadratic computational cost associated with particle interactions to a near-linear cost. The essence of these algorithms lies in the random partitioning of the particle ensemble into smaller batches at each time step. The interaction of each particle within these batches is then evolved until the subsequent time step. This approach effectively decreases the computational cost by an order of magnitude while increasing the amount of fluctuations due to the random partitioning. In this work, we propose a variance reduction technique for RBM applied to nonlocal PDEs of Fokker-Planck type based on a control variate strategy. The core idea is to construct a surrogate model that can be computed on the full set of particles at a linear cost while maintaining enough correlations with the original particle dynamics. Examples from models of collective behavior in opinion spreading and swarming dynamics demonstrate the great potential of the present approach.

Quantum System Dynamics: Harnessing Constructive Resonance for Technological Advancements, Universal Matter Creation and Exploring the Paradigm of Resonance-induced Gravity

The complex dynamics of constructive resonance are the main topic of this quantum physics study, along with its implications for matter generation, the unification of quantum and classical knowledge, and important technological developments. Space-time is conceptualized in terms of an interwoven fabric in which both linear and non-linear patterns are recorded in an information field. According to this paradigm, basic particle interactions that result in the development of the material universe are referred to as "Constructive Resonance Waves." A five-dimensional cosmos is shaped by the introduction of Cosmic Information (CI), which is essential since it is a basic base vector related to the dimensions of space and time. The Resonance-Induced Information Force Field (RIIFF) and Constructive Resonance are two new theoretical concepts that are introduced in this paper.

Probing the interactions of axion-like particles with electroweak bosons and the Higgs boson in the high energy regime at LHC

We study the interactions of axion-like particles (ALPs) with the Standard Model particles, aiming to probe their phenomenology via non-resonant searches at the LHC. These interactions are mediated by higher dimensional effective operators within two possible frameworks of linearly and non-linearly realised electroweak symmetry breaking. We consider the ALPs to be light enough to be produced on-shell and exploit their derivative couplings with the SM Higgs boson and the gauge bosons. We will use the high momentum transfer processes, namely hZ, Zγ, WW and WWγ production from pp collisions. We derive upper limits on the gauge-invariant interactions of ALPs with the electroweak bosons and/or Higgs boson that contribute to these processes, from the re-interpretation of the latest Run 2 available LHC data. The constraints we obtain are strong for ALP masses below 100 GeV. These allowed effective interactions in the ALP parameter space yield better significance at HL-LHC and thus, offer promising avenues for subsequent studies. Furthermore, we augment our cut-based analysis with gradient-boosted decision trees, which improve the statistical significance distinctly across these interaction channels. We briefly compare the results with the complementary probe of these couplings via direct production of ALPs in association with the Higgs boson or a vector boson.

Neural-network quantum states for ultra-cold Fermi gases

Ultra-cold Fermi gases exhibit a rich array of quantum mechanical properties, including the transition from a fermionic superfluid Bardeen-Cooper-Schrieffer (BCS) state to a bosonic superfluid Bose-Einstein condensate (BEC). While these properties can be precisely probed experimentally, accurately describing them poses significant theoretical challenges due to strong pairing correlations and the non-perturbative nature of particle interactions. In this work, we introduce a Pfaffian-Jastrow neural-network quantum state featuring a message-passing architecture to efficiently capture pairing and backflow correlations. We benchmark our approach on existing Slater-Jastrow frameworks and state-of-the-art diffusion Monte Carlo methods, demonstrating a performance advantage and the scalability of our scheme. We show that transfer learning stabilizes the training process in the presence of strong, short-ranged interactions, and allows for an effective exploration of the BCS-BEC crossover region. Our findings highlight the potential of neural-network quantum states as a promising strategy for investigating ultra-cold Fermi gases.

DARWIN/XLZD: A future xenon observatory for dark matter and other rare interactions

The DARWIN/XLZD experiment is a next-generation dark matter detector with a multi-ten-ton liquid xenon time projection chamber at its core. Its principal goal will be to explore the experimentally accessible parameter space for Weakly Interacting Massive Particles (WIMPs) in a wide mass-range, until interactions of astrophysical neutrinos will become an irreducible background. The prompt scintillation light and the charge signals induced by particle interactions in the liquid xenon target will be observed by VUV-sensitive, ultra-low background photosensors. Besides its excellent sensitivity to WIMPs with masses above ∼5 GeV, such a detector with its large mass, low-energy threshold and ultra-low background level will also be sensitive to other rare interactions, and in particular also to bosonic dark matter candidates with masses at the keV-scale. We present the detector concept, discuss the main sources of backgrounds, the technological challenges and some of the ongoing detector design and R&D efforts, as well as the large-scale demonstrators. We end by discussing the sensitivity to particle dark matter interactions.

Evaluating 3-parameter packing model with discrete element modeling

Accurate prediction of particle packing density remains challenging. Herein, the particle packing is simulated by discrete element modeling and the packing density results are used to evaluate the 3-parameter particle packing model. When the 3-parameter model is applied to binary and ternary blended mixes, the mean absolute errors in packing density prediction are 0.96% and 1.37%, respectively. Overall, the accuracy of the 3-parameter model is very good when applied to binary blends but not as good when applied to ternary blends, especially when the intermediate size particles are dominant. The discrete element modeling reveals that even when the intermediate size particles are dominant, there are significant particle interactions between the smaller size and larger size particles, which have not been properly accounted for in the existing packing models. Hence, there is still room for improving the existing packing models, requiring further discrete element modeling to study particle interactions.

Which Coverages of Arc-Shaped Proteins Are Required for Membrane Tubulation?

Arc-shaped BIN/Amphiphysin/Rvs (BAR) domain proteins generate curvature by binding to membranes and induce membrane tubulation at sufficiently large protein coverages. For the amphiphysin N-BAR domain, Le Roux et al., Nat. Commun. 2021, 12, 6550, measured a threshold coverage of 0.44 ± 0.097 for nanotubules emerging from the supported lipid bilayer. In this article, we systematically investigate membrane tubulation induced by arc-shaped protein-like particles with coarse-grained modeling and simulations and determine the threshold coverages at different particle-particle interaction strengths and membrane spontaneous curvatures. In our simulations, the binding of arc-shaped particles induces a membrane shape transition from spherical vesicles to tubules at a particle threshold coverage of about 0.5, which is rather robust to variations of the direct attractive particle interactions or spontaneous membrane curvature in the coarse-grained model. Our study suggests that threshold coverages of around or slightly below 0.5 are a general requirement for membrane tubulation by arc-shaped BAR domain proteins.