Number Of Active Particles Research Articles

ВИЗНАЧЕННЯ ВПЛИВУ ВНУТРІШНІХ ЕНЕРГІЙ КРИСТАЛІЧНОЇ РЕШІТКИ НА ОТРИМАННЯ НАНОСТРУКТУР У ПОВЕРХНЕВИХ ШАРАХ АЛЮМІНІЄВИХ СПЛАВІВ

The paper presents the results of calculating the crystallization energy and examines its influence on the size of the nanostructured grain during ion-plasma treatment of aluminum (VD17) with oxygen and nitrogen ions. To address this task, we employ a previously proposed model, which considers the impact of individual ions on thermal conductivity and thermoelasticity in the affected area, taking into account their energy, charge, and type. Initially, we estimate the potential number of particles in the nanostructure. Then, we compute the energy required for atomizing the grain from atoms and chemical compounds. By determining the total atomization energy of the grain (Eas), we establish the necessary energy for its formation (Es = 1.1Eas). This energy enables the determination of all characteristics in the ion's action area, such as temperature, temperature rise rate, thermal stresses, strain rate, grain size, volume, and depth of the nanostructure, as well as the actual number of particles in the nanostructure. The calculations demonstrate that the crystallization energy increases the ion energy required to obtain nanostructures. At energies close to 3∙102 eV, it ranges from 0.1 to 7 eV, which can be disregarded, while at energies close to 1.6∙104 eV, crystallization energy ranges from 2.1∙102 to 1.2∙104 eV, with higher values for oxygen ions. Additionally, the calculations show that ion charge significantly affects crystallization energy; for large ion charges, it increases. All of this underscores the necessity of considering crystallization energy only at energies of 2∙103 – 2∙104 eV, allowing refinement of the technological parameters of ion-plasma treatment of aluminum alloys to increase the likelihood of obtaining nanostructures. Furthermore, the ability to determine the sizes of nanostructures allows predicting the physical and mechanical characteristics of surface layers of processed materials. These studies may be of interest to specialists involved in surface strengthening of aluminum alloy surfaces and further research into nanostructures

Mechanical properties, pore characteristics and microstructure of modified magnesium slag cemented coal-based solid waste backfill materials: Affected by fly ash addition and curing temperature

The high-temperature, deep-well environment can affect the mechanical properties and long-term stability of modified magnesium slag cemented coal-based solid waste backfill material (MMS-CBM). The purpose of this study was to investigate the effects of fly ash addition (0 %, 10 %, 20 %, 30 % and 40 %) and curing temperature (20 °C, 30 °C and 40 °C) on the mechanical properties, pore characteristics and microstructure of MMS-CBM. Based on this, relevant laboratory tests (uniaxial compressive strength test, pore structure test and microstructure test) were conducted to characterize the influence mechanism of fly ash addition and curing temperature on the performance of MMS-CBM. The results show that the physical properties (uniaxial compressive strength, pore characteristics and microstructure) of MMS-CBM are significantly affected by fly ash addition and curing temperature. With the increase of fly ash addition, the number of active particles and hydration products involved in the hydration reaction gradually increased, and the physical properties of MMS-CBM were gradually optimized. With the increase of curing temperature, the hydration reaction rate and hydration reaction degree of MMS-CBM gradually deepened, which accelerated the volcanic ash reaction of fly ash particles, which had a promoting effect on the early intensity of MMS-CBM. However, the subsequent strength of MMS-CBM will be affected by thermal damage, resulting in deterioration of physical properties and seriously affecting the long-term stability of MMS-CBM. In addition, the porosity and fractal dimension of MMS-CBM are linearly related to the uniaxial compressive strength, indicating that the pore characteristics can reflect the mechanical properties of MMS-CBM. This study provides a theoretical reference value for the application of MMS-CBM in high-temperature deep wells.

Large-scale convective flow sustained by thermally active Lagrangian tracers

Non-isothermal particles suspended in a fluid lead to complex interactions – the particles respond to changes in the fluid flow, which in turn is modified by their temperature anomaly. Here, we perform a novel proof-of-concept numerical study based on tracer particles that are thermally coupled to the fluid. We imagine that particles can adjust their internal temperature reacting to some local fluid properties, and follow simple, hard-wired active control protocols. We study the case where instabilities are induced by switching the particle temperature from hot to cold depending on whether it is ascending or descending in the flow. A macroscopic transition from stable to unstable convective flow is achieved, depending on the number of active particles and their excess negative/positive temperature. The stable state is characterized by a flow with low turbulent kinetic energy, strongly stable temperature gradient, and no large-scale features. The convective state is characterized by higher turbulent kinetic energy, self-sustaining large-scale convection, and weakly stable temperature gradients. Individually, the particles promote the formation of stable temperature gradients, while their aggregated effect induces large-scale convection. When the Lagrangian temperature scale is small, a weakly convective laminar system forms. The Lagrangian approach is also compared to a uniform Eulerian bulk heating with the same mean injection profile, and no such transition is observed. Our empirical approach shows that thermal convection can be controlled by pure Lagrangian forcing, and opens the way for other data-driven particle-based protocols to enhance or deplete large-scale motion in thermal flows.

On the Use of Microscale Abrasion Test for Determining the Particle Abrasivity

Abstract Particle abrasivity is an important concept for helping to select materials for pumps and for disc cutters in underground excavation, and specific ASTM standards are available for making these selections. However, for manufacturing processes in which abrasive action is their core, the particle size range is approximately a few micrometers. The evaluation of particle abrasivity using the microscale abrasion test matches this range of particles for this purpose, but relatively few investigations using this kind of method have been conducted. The aim of this investigation is to use the microscale abrasion test to evaluate the particle abrasivity, avoiding changes on the ball surface and on the particle size distribution. Samples of quenched AISI D2 tool steel were used for tests. The wear mode was dependent on the testing time. Alumina (Al2O3) particles presented a lower abrasiveness when compared to boron carbide (B4C) ones, confirmed by the higher wear coefficient found in the latter after reaching the steady-state regime. This behavior was evidenced by the number of active particles in the contact, which showed that there were a larger number of B4C particles than Al2O3 during the contact at all sliding distances. The particle abrasivity is discussed in terms of significant characteristics of slurries: particle shape, particle size distribution, hardness-to-elastic modulus ratio, zeta potential, and density. As the controlling of those characteristics seems to be very important, particle abrasivity is a concept that needs to be improved besides the test system used for that purpose.

Impact of Microwave Plasma Torch on the Yeast Candida glabrata

Recently, various cold plasma sources have been tested for their bactericidal and fungicidal effects with respect to their application in medicine and agriculture. The purpose of this work is to study the effects of a 2.45 GHz microwave generated plasma torch on a model yeast example Candida glabrata. The microwave plasma was generated by a surfatron resonator, and pure argon at a constant flow rate of 5 Slm was used as a working gas. Thanks to a high number of active particles generated in low-temperature plasma, this type of plasma has become highly popular, especially thanks to its bactericidal effects. However, its antimycotic effects and mechanisms of fungal inactivation are still not fully understood. Therefore, this study focuses on the antifungal effects of the microwave discharge on Candida glabrata. The main focus is on the measurement and evaluation of changes in inactivation effects caused by varying initial concentration of Candida glabrata cells, applied microwave power and exposure time. The discharge was applied on freshly inoculated colonies of Candida glabrata spread on the agar plates and its inhibitory effects were observed in the form of inhibition zones formed after the subsequent cultivation.

Incremental update of electrostatic interactions in adaptively restrained particle simulations

The computation of long-range potentials is one of the demanding tasks in Molecular Dynamics. During the last decades, an inventive panoply of methods was developed to reduce the CPU time of this task. In this work, we propose a fast method dedicated to the computation of the electrostatic potential in adaptively restrained systems. We exploit the fact that, in such systems, only some particles are allowed to move at each timestep. We developed an incremental algorithm derived from a multigrid-based alternative to traditional Fourier-based methods. Our algorithm was implemented inside LAMMPS, a popular molecular dynamics simulation package. We evaluated the method on different systems. We showed that the new algorithm's computational complexity scales with the number of active particles in the simulated system, and is able to outperform the well-established Particle Particle Particle Mesh (P3M) for adaptively restrained simulations. © 2018 Wiley Periodicals, Inc.

Numerical and Experimental Investigation of the Influence of Growth Restriction on Grain Size in Binary Cu Alloys

Grain refinement by elemental addition has been extensively investigated within the last decades in Al or Mg alloys. In contrast, in the Cu system, the role of solute on grain size is less investigated. In this study, the grain refinement potency of several alloying elements of the Cu system was examined. To predict grain size depending on the growth restriction factor Q, grain size modelling was performed. The results obtained by the grain size model were compared to variations in the grain size of binary Cu alloys with increasing solute content under defined cooling conditions of the TP-1 grain refiner test of the Aluminium Association©. It was found that the experimental results differed significantly from the predicted grain size values for several alloying elements. A decreasing grain size with increasing alloy concentration was observed independently of the growth restriction potency of the alloying elements. Furthermore, excessive grain coarsening was found for several solutes beyond a transition point. It is assumed that contradictory variations in grain size result from a change in the nucleating particle density of the melt. Significant decreases in grain size are supposed to be due to the in-situ formation of potent nucleation sites. Excessive grain coarsening with increasing solute content may occur due to the removal of nucleating particles. The model shows that the difference in the actual number of particles before and beyond the transition point must be in the range of several orders of magnitude.

Shape and Displacement Fluctuations in Soft Vesicles Filled by Active Particles.

We investigate numerically the dynamics of shape and displacement fluctuations of two-dimensional flexible vesicles filled with active particles. At low concentration most of the active particles accumulate at the boundary of the vesicle where positive particle number fluctuations are amplified by trapping, leading to the formation of pinched spots of high density, curvature and pressure. At high concentration the active particles cover the vesicle boundary almost uniformly, resulting in fairly homogeneous pressure and curvature, and nearly circular vesicle shape. The change between polarized and spherical shapes is driven by the number of active particles. The center-of-mass of the vesicle performs a persistent random walk with a long time diffusivity that is strongly enhanced for elongated active particles due to orientational correlations in their direction of propulsive motion. In our model shape-shifting induces directional sensing and the cell spontaneously migrate along the polarization direction.

Particle Radius Distribution Model-Based Analysis of PEFC Cathode Catalyst Degradation Mechanisms

One of the main obstacles for the commercialization of polymer electrolyte fuel cells (PEFC) is degradation. A major source for performance decline is the cathode catalyst layer. The continuous optimization of the compound catalyst layer towards lower catalyst loading, higher mass activity and better electrochemical performance on the one hand has increased degradation and performance decline on the other hand. In state-of-the-art nanoparticle based catalysts, this decline of the performance is linked to a loss of electrochemically active surface area (ECSA) over time [1]. Furthermore, this ECSA loss was found to correlate to changes in the catalyst’s particle radius distribution (PRD) [2]. There are three mechanisms that could be responsible to changes in the particle radius distribution: 1. Ostwald ripening, i.e. dissolution of especially the smaller, less stable particles and redeposition predominantly on larger particles; 2. Coagulation of particles, i.e. merging of two smaller particles forming a bigger particle and thus decreasing the overall surface energy; 3. Inactivation of particles, e.g. by detachment from the carbon substrate, loss of electronic or ionic connection or by passivating with impurities. These degradation mechanisms lead to a decrease of ECSA and thus to a loss in specific activity of the catalyst. The current work attempts to link experimentally observed ECSA loss to the proposed degradation mechanisms. The presented model [3-7] combines the Lifshitz- Slyozov-Wagner theory for dissolution and redeposition [4,5] with Smoluchowski’s coagulation theory [6] and includes a simple deactivation term [7]. The model is able to describe temporal changes in the particle radius distribution and its moments, i.e. the number of active particles, mean particle radius, electrochemically active surface area and the active Pt mass. Properly parametrized, this model is able to give valuable insight into the structural changes in the catalyst layer that occur during PEFC degradation. In order to parametrize the model, it was fitted to experimental results of accelerated stress tests (AST, see Fig. 1) [3] that were performed under different conditions (temperature, pH, upper potential limit and waveform of the potential). It was attempted to identify the prevailing mechanism(s) and determine the kinetic parameters of the degradation process under these conditions. However, ambiguities in the fits were found, i.e. different sets of parameters corresponding to different physical scenarios could fit the experimental data. Those scenarios as well as their origins, likelihood and implications under different conditions will be discussed systematically in this talk.

The Law of Large Numbers for the Number of Active Particles in an Epidemic Model

In the last decade, a large number of papers was devoted to studying probabilistic properties of epidemic models on graphs. In this paper we consider a generalization of the model proposed by Machado, Mashurian, and Matzinger. The Machado--Mashurian--Matzinger model serves as an interpretation of spread of viruses in a computer network. We assume that at each moment of time more than one node of the network can be infected. In this context we propose a more advanced model permitting jumps of several particles each time, while the number of such particles is random. We prove the optimal version of the law of large numbers for the number of infected particles in the epidemic model at hand.

An adaptive sample count particle filter

The particle filter technique has been used extensively over the past few years to track objects in challenging environments. Due to its nonlinear nature and the fact that it does not assume a Gaussian probability density function it tends to outperform other available tracking methods. A novel adaptive sample count particle filter (ASCPF) tracking method is presented in this paper for which the main motivation is to accurately track an object in crowded scenes using fewer particles and hence with reduced computational overhead. Instead of taking a fixed number of particles, a particle range technique is used where an upper and lower bound for the range is initially identified. Particles are made to switch between an active and inactive state within this identified range. The idea is to keep the number of active particles to a minimum and only to increase this as and when required. Active contours are also utilized to determine a precise area of support around the tracked object from which the color histograms used by the particle filter can be accurately calculated. This, together with the variable particle spread, allows a more accurate proposal distribution to be generated while using less computational resource. Experimental results show that the proposed method not only tracks the object with comparable accuracy to existing particle filter techniques but is up to five times faster.

Challenges and Mechanisms of CMP Slurries for 32nm and Beyond

CMP slurries for 32nm and beyond are required to effectively planarize surfaces with fine and delicate device patterns without causing any nanodefects, without contributing nanocontaminants, and without generating atomic-level-roughness. Key solutions to these challenges are material removal using homogeneous and efficient mechanical action, surface protection using appropriate additives, and thorough contamination control (from large particles to dissolved gasses and light). The important parameter for mechanical action with abrasives is friction energy. Key factors to increase friction energy are: i) the number of active particles, ii) the contact area of each particle, and iii) the friction coefficient of each particle. These factors can be controlled with size, shape, morphology or surface charge of abrasive particles. Controlling abrasive shape and surface charge are especially important to achieve higher removal rate.

Exponential Distributions of Collective Flow-Event Properties in Viscous Liquid Dynamics

We study the statistics of flow events in the inherent dynamics in supercooled two- and three-dimensional binary Lennard-Jones liquids. Distributions of changes of the collective quantities energy, pressure, and shear stress become exponential at low temperatures, as does that of the event "size" S identical with summation operator[under ][over ]d_{i};{2}. We show how the S distribution controls the others, while itself following from exponential tails in the distributions of (1) single particle displacements d, involving a Lindemann-like length d_{L} and (2) the number of active particles (with d>d_{L}).

Asymptotic regimes and structure of concentration tails in the Dykhne model

A transport problem is solved for a high-contrast regularly inhomogeneous medium. Transport regimes and structure of the concentration tails in high-permeability regions are analyzed for two geometries of such regions: a plane layer and a right cylinder. It is shown that changes with time of transport regimes lead to complex asymptotic particle distributions at long distances (concentration “tails”). The time dependence of the total number of active particles and depth of particle penetration into the low-permeability region are calculated.

Number-concentration of nanoparticles in liposomal and polymeric multiparticulate preparations: Empirical and calculation methods

The actual number of particles in formulations of nanoparticles (NP) is of importance for quality assurance, comprehensive physicochemical characterization, and pharmacodynamics. Some calculation methods that have been previously employed are limited because they rely on several assumptions and are not applicable for certain preparations. Currently there are no validated experimental methods for determining the particle number-concentration ( N c) of liposomal and polymeric nanoparticulate preparations (<500 nm). This study examines a new empirical method for counting the number of particles in nanoparticulate formulations including drug-containing liposomes and polymeric NP. In the new method, suspended NP are nebulized to form aerosol droplets which are dried and counted using a scanning mobility particle sizer (SMPS). Experiments were conducted with three different preparations, empty liposomes (200 and 400 nm), drug-loaded liposomes (200 nm), and polymeric NP (150 nm). It was verified that no detrimental morphological or structural changes of the formulations have been induced by the SMPS technique, and that the obtained N c values represent the original particles. It is concluded that nano-formulations with concentrations of up to 10 7 particles per 1 cm 3 air, corresponding to approximately 10 12 particles per 1 ml solution, can be directly counted within the size range of 30–900 nm. The measured values are compared to newly developed theoretical calculations to assess the viability of these calculations.

Pad Surface Roughness and Slurry Particle Size Distribution Effects on Material Removal Rate in Chemical Mechanical Planarization

The ability to predict material removal rates in chemical mechanical planarization (CMP) is an essential ingredient for low cost, high quality IC chips. Recently, models that address the slurry particles have been proposed. We address three such models. The first two differ only in how the number of active particles is computed. Both assume that pad asperities are identical and nonrandom. The third is dynamic in accommodating changing pad properties. For larger mean particle size (diameter), the role of the standard deviation of particle size distribution is uncertain. The dynamic behavior of the third model is compared with experimental observations.

Characterization and mechanical modeling of the abrasion properties of sintered tools with embedded hard particles

A wide variety of applications, ranging from rough cutting of stone and concrete to ultra-precision machining of ceramics for electronic components, are commonly performed with the so-called super-abrasive tools. The working part of such tools is made of hard particles, typically diamonds or cubic boron nitride crystals, embedded in a resin or sintered metal matrix. The performance of the tool is influenced by many technological aspects, but basically depends on the abrasion property of the hard particles-matrix system. In the present paper, a mechanical approach is followed in order to link the performance of a tool to some relevant design parameters, i.e. hard particle content and diameter. The model is based both on theoretical and experimental evidences. An experimental technique is described for the tool characterization, based on a coupled optical and laser-scanner acquisition of the tool working-surface. Moreover, the tool design parameters are put into play through a stereological model. The numerical strategy of the presented model is justified by a preliminary study of the contact stress distribution over the contact area. Different useful parameters (i.e. distribution of contact stresses, number of active particles, etc.) are obtained from the numerical simulation of abrasion, although the performance of the tool is primarily evaluated from the estimated removed volume.

Computer-Aided Simulation of Porous Electrodes of a Filled-up Type

In the paper, computer-aided simulation of porous electrodes of a filled-up type is done using two-dimensional lattices as an example. The attention is mainly focused on the simulation of porous electron-conducting substrates that are required to put the catalyst particles on. The principal parameter of the system is the share of the electron-conducting particles of the substrate. Calculated are the share of the electron-conducting particles of the substrate (a conducting cluster), the distribution of this quantity over the electrode thickness, and the number of exits made by a conducting cluster onto the rear surface of the electrode. The notion of transparency is introduced. The perimeter of a conducting cluster is determined. The number of active particles of a catalyst is found out. Two versions of the electrode functioning are investigated for catalysts-enzymes. In one version the electrochemical process proceeds no matter the position of the enzyme molecules. In the other, the electrochemical process takes place provided certain conditions of contact between enzyme molecules and a conducting cluster are ensured. Established is the region of optimum concentrations of components at which the electrochemical activity of the electrode is maximum.

The A dependence and threshold behaviour of the inclusive (π ,2π) reaction for T=0 nuclei

The author calculates the dependence of the energy-differential inclusive cross section for the ( pi ,2 pi ) reaction on the mass number A for N=Z nuclei up to A approximately 60. He also calculates the variations of this cross section near threshold, where the outgoing pions have almost zero energy. He finds a significant A dependence resulting from the dominance of the increase in number of active particles over the decrease of matrix element squared. The threshold behaviour is strongly affected by Coulomb distortions of the outgoing pions, and he finds a large difference between the ( pi +,2 pi +) and the ( pi +, pi - pi +) cases. The true absorption of final pions is also checked, and found to be of secondary importance. All cases are studied as a function of g', the Migdal spin-isospin parameter.

Comparison of upper and lower bound methods using a soluble many-Fermion model

Upper bounds, lower bounds, and estimates based on moments are compared for the ground state energy of a soluble Hamiltonian due to Lipkin. Several bounding methods based on variational approaches and one based on the method of moments are employed. We show that lower bounds are of comparable quality with upper bounds and are no more difficult to obtain. No single bounding method is found superior over the entire range of parameters we study for the soluble Hamiltonian. However, in one region we find an upper bound from one method which coincides with the lower bound of another method, thus yielding the exact ground state energy. We also show that estimation methods based on the easily calculated first and second moments of the eigenvalue distribution are surprisingly accurate for a wide range of coupling parameters and number of active particles.