Properties Of Primary Particles Research Articles

Spray Flame Synthesis and Multiscale Characterization of Carbon Black-Silica Hetero-Aggregates.

The increasing demand for lithium-ion batteries requires constant improvements in the areas of production and recycling to reduce their environmental impact. In this context, this work presents a method for structuring carbon black aggregates by adding colloidal silica via a spray flame with the goal of opening up more choices for polymeric binders. The main focus of this research lies in the multiscale characterization of the aggregate properties via small-angle X-ray scattering, analytical disc centrifugation and electron microscopy. The results show successful formation of sinter-bridges between silica and carbon black leading to an increase in hydrodynamic aggregate diameter from 201 nm to up to 357 nm, with no significant changes in primary particle properties. However, segregation and coalescence of silica particles was identified for higher mass ratios of silica to carbon black, resulting in a reduction in the homogeneity of the hetero-aggregates. This effect was particularly evident for silica particles with larger diameters of 60 nm. Consequently, optimal conditions for hetero-aggregation were identified at mass ratios below 1 and particle sizes around 10 nm, at which homogenous distributions of silica within the carbon black structure were achieved. The results emphasise the general applicability of hetero-aggregation via spray flames with possible applications as battery materials.

Ozone-oxidized black carbon particles change macrophage fate: Crosstalk between necroptosis and macrophage extracellular traps

The impacts of environmental PM 2.5 on public health have become a major concern all over the world. Many studies have shown that PM 2.5 still poses a threat to public health even at very low levels. Physical or chemical reactions occur between primary particles and other components in the environment, which changes the properties of primary particles. Such newly formed particles with changed properties are called secondary particles. Ozone-oxidized black carbon (oBC) is a key part of PM 2.5 and a representative secondary particle. Macrophages extracellular traps (METs) is a means for macrophages to capture and destroy invading pathogens, thereby exercising innate immunity. Necroptosis is a kind of programmed cell death, which is accompanied by the destruction of membrane integrity, thus inducing inflammatory reaction. However, there is no research on the crosstalk mechanism between necroptosis and MET after oBC exposure. In our study, AO/EB staining, SYTOX Green staining, fluorescent probe, qPCR, Western blot, and immunofluorescence were applied. This experiment found that under normal physiological conditions, when macrophages receive external stimuli (such as pathogens; in our experiment: phorbol 12-myristate 13-acetate (PMA)), they will form METs, capture and kill pathogens, thus exerting innate immune function. However, exposure to oBC can cause necroptosis in macrophages, accompanied by increased levels of reactive oxygen species (ROS) and cytosolic calcium ions, as well as the expression disorder of inflammatory factors and chemokines, and prevent the formation of METs, lose the function of capturing and killing pathogens, and weaken the innate immune function. Notably, inhibition of necroptosis restored the formation of METs, indicating that necroptosis inhibited the formation of METs. This study was the first to explore the crosstalk mechanism between necroptosis and METs after oBC exposure.

Study of identified particle ratios using cosmic rays Monte-Carlo models in [formula omitted] collisions at [formula omitted] and 7 TeV

Cosmic rays with high energies can be studied only by measuring the extensive air showers of particles produced in the upper atmosphere. A complete simulation is required to know the primary particle properties, which is possible by studying the modeling of hadronic particle production at the generator level. In this connection, we report the yield ratios π−/π+, K−/K+, p̄/p (same particles ratio), p/π, p/K, and K/π (different particles ratio) with pseudorapidity (η) in pp collisions at s = 0.9 and 7 TeV using models being used for extensive air shower simulation. The ratios were measured at the following transverse momentum (pT) regions; low pT; 0 < pT< 0.8 GeV/c, intermediate pT; 0.8 < pT< 1.2 GeV/c and high pT; pT> 1.2 GeV/c and at different pseudorapidity (η) range of 3.0 < η< 4.5 and 2.5 < η< 4.5. These results are then compared with the data from the LHCb experiment. The ratio of π−/π+ from various model predictions agrees with the measurements at both energies at almost all pT and η regions. There is a reasonable agreement in K−/K+ and p̄/p ratios of model and experimental data at s = 900 GeV except few pT and η regions, in which the models do not describe the experimental data adequately. However, almost all the models fully describe the K−/K+ and p̄/p ratios at s = 7 TeV except few pT and η regions. Moreover, none of the models completely reproduce the different particle ratios at s = 900 GeV, with Pythia and EPOS producing better results. On the other hand, in most cases, the models’ predictions for the different particle ratios are consistent with experimental data s = 7 TeV. These kinds of studies will certainly help tune the Monte-Carlo generators being used for the studies of the hadron productions at various energies.

Using Deep Learning in Ultra-High Energy Cosmic Ray Experiments

The extremely low flux of ultra-high energy cosmic rays (UHECR) makes their direct observation by orbital experiments practically impossible. For this reason all current and planned UHECR experiments detect cosmic rays indirectly by observing the extensive air showers (EAS) initiated by cosmic ray particles in the atmosphere. Various types of shower observables are analyzed in the modern UHECR experiments including a secondary radio signal and fluorescent light from the excited nitrogen molecules. Most of the data is collected by the network of surface stations which allows to measure the lateral EAS profile. The raw observables in this case are the time-resolved signals for the set of adjacent triggered stations. The Monte Carlo shower simulation is performed in order to recover the primary particle properties. In traditional techniques the MC simulation is used to fit some synthetic observables such as the shower rise time, the shower front curvature and the particle density normalized to a given distance from the core. In this talk we’ll consider an alternative approach based on the deep convolutional neural network trained on a large Monte-Carlo dataset, using the detector signal time series as an input. The above approach has proven its efficiency with the Monte-Carlo simulations of the Telescope Array Observatory surface detector. We’ll discuss in detail how the network architecture is optimized for this particular task.

Biomass-burning-derived particles from a wide variety of fuels – Part 1: Properties of primary particles

Abstract. Relationships between various optical, physical, and chemical properties of biomass-combustion-derived particles are characterized for particles produced in the laboratory from a wide range of fuels and burn conditions. The modified combustion efficiency (MCE), commonly used to parameterize biomass particle emissions and properties, is shown to generally have weak predictive capabilities, especially for more efficient combustion conditions. There is, however, a strong relationship between many intensive optical properties (e.g., single-scatter albedo, Ångström absorption exponent, mass absorption efficiency) and the organic aerosol-to-black carbon ([OA] ∕ [BC]) mass ratio over a wider range than previously considered (0.3 to 105). The properties of brown carbon (BrC, i.e., light-absorbing organic carbon) also vary with [OA] ∕ [BC]. Coating-induced enhancements (i.e., “lensing” effects) contribute only a minor amount to BC absorption for all of the burns despite some burns producing particles having large ensemble-average coating-to-core mass ratios. The BC–OA mixing state varies strongly with [OA] ∕ [BC]; the fraction of OA that is internally mixed with BC decreases with [OA] ∕ [BC] while the relative amount of OA coated on BC increases. In contrast, there is little relationship between many OA bulk chemical properties and [OA] ∕ [BC], with the O : C and H : C atomic ratios and the relative abundance of a key marker ion (m/z=60, linked to levoglucosan) all showing no dependence on [OA] ∕ [BC]. In contrast, both the organic nitrate fraction of OA and the OA volatility do depend on the [OA] ∕ [BC]. Neither the total particle nor BC-specific size distributions exhibit any clear dependence on the burn conditions or [OA] ∕ [BC], although there is perhaps a dependence on fuel type. Overall, our results expand on existing knowledge to contribute new understanding of the properties of particles emitted from biomass combustion.

Numerical Study of Soft Colloidal Nanoparticles Interaction in Shear Flow.

The mechanical behavior of nanoparticle assemblies depends on complex particle interactions that are difficult to study experimentally. Depending on the nanoparticle morphology, these interactions could lead to adhesive and elastic-plastic behavior during contact deformation. The aim of this research is to study the effect of contact interactions between polymer nanoparticles and their impact on the macroscopic properties of formed aggregates. For this purpose, the discrete element method (DEM) was used to develop an interaction model combining elastic-plastic deformation and adhesion to study the behavior of spherical polymeric nanoparticles. Initially, a pair of particles interacting in the normal direction was simulated to evaluate the effect of adhesion and plastic deformation in the pull-off force of the contact. Based on these results, the simulations were extended to a dispersed system of nanoparticles, in which multibody interactions become dominant. Considering the aggregation between the nanoparticles induced by a shear flow, we performed an analysis of the number of aggregates and aggregates size in time to characterize the strength of clusters formed during the process. The simulation results showed that the interaction strength upon breakage of the clusters, correlating with the aggregates size, depends on the nanoparticle's softness. In this way, we verified that the type of contact interaction directly influences the macroscopic mechanical response of nanoparticle assemblies. Therefore, our model represents a new way of predicting the mechanical behavior of polymer nanoparticle systems and of optimizing it by adjusting primary particle properties.

Morphology, composition, and mixing state of primary particles from combustion sources \u2014 crop residue, wood, and solid waste

Morphology, composition, and mixing state of individual particles emitted from crop residue, wood, and solid waste combustion in a residential stove were analyzed using transmission electron microscopy (TEM). Our study showed that particles from crop residue and apple wood combustion were mainly organic matter (OM) in smoldering phase, whereas soot-OM internally mixed with K in flaming phase. Wild grass combustion in flaming phase released some Cl-rich-OM/soot particles and cardboard combustion released OM and S-rich particles. Interestingly, particles from hardwood (pear wood and bamboo) and softwood (cypress and pine wood) combustion were mainly soot and OM in the flaming phase, respectively. The combustion of foam boxes, rubber tires, and plastic bottles/bags in the flaming phase released large amounts of soot internally mixed with a small amount of OM, whereas the combustion of printed circuit boards and copper-core cables emitted large amounts of OM with Br-rich inclusions. In addition, the printed circuit board combustion released toxic metals containing Pb, Zn, Sn, and Sb. The results are important to document properties of primary particles from combustion sources, which can be used to trace the sources of ambient particles and to know their potential impacts in human health and radiative forcing in the air.

A study of radio frequency spectrum emitted by high energy air showers with LOFAR

The LOw Frequency ARray (LOFAR) is a multipurpose radio antenna array aimed to detect radio signals in the frequency range 10 - 240 MHz, covering a large surface in Northern Europe with a higher density in the Northern Netherlands. The detection of the radio signal emitted by extensive air showers allows to reconstruct the geometry of the observed cascade. Thus, several properties of primary particles (e.g. arrival direction, mass composition) can be inferred. We describe a study of several geometrical parameters of the radio signal emitted by extensive air showers propagating in the atmosphere, and their correlation with the observed radio frequency spectrum. In order to find the best parameters that describe the correlation between primary cosmic ray information and the emitted radio signal, a preliminary study on simulated events has been done. Monte Carlo simulations of radio signals have been produced by using the CoREAS code, a plug-in of the CORSIKA particle simulation code. The final aim of this study is to find a method to infer information of primary cosmic rays in an independent way from the well-established fluorescence and surface detector techniques, in view of affirming the radio detection technique as reliable method for the study of high energy cosmic rays.

Constraints on high energy interaction models from LHC and cosmic ray data

Predictions of popular cosmic ray interaction models for some basic character- istics of cosmic ray-induced extensive air showers are analyzed in view of experimental data on proton-proton collisions, obtained at the Large Hadron Collider. The differences between the results are traced down to different approaches for the treatment of hadronic interactions, implemented in those models. Potential measurements by LHC and cosmic ray experiments, which could be able to discriminate between the alternative approaches, are proposed. Modeling of high energy hadronic interactions is of considerable importance for experimental studies at the Large Hadron Collider (LHC) and, especially, in high energy cosmic ray (CR) field. In the latter case, one traditionally relies on the extensive air shower (EAS) techniques: the properties of primary CR particles are reconstructed from measured characteristics of nuclear-electro-magnetic cascades induced by CR interactions in the atmosphere. This naturally implies the importance of detailed Monte Carlo simulations of EAS development, particularly, of its backbone - the cascade of nuclear interactions of both the primary particles and of secondary hadrons produced. Thus, the success of the experimental studies depends on the validity of hadronic interaction models used in the analysis. One usually chooses between two main experimental procedures (1). In the first case, one deals with the information obtained with scintillation detectors positioned at ground. The energy of the pri- mary particle is reconstructed from the measured lateral density of charged particles (mostly electrons and positrons) while the particle type is inferred from the relative fraction of muons, compared to all charged particles at ground. Alternatively, one may study the longitudinal EAS development by mea- suring fluorescence light produced by excited air molecules at different heights in the atmosphere, for which purpose dedicated fluorescence telescopes are employed. The primary energy is then related to the total amount of fluorescence light emitted. In turn, the particle type may be determined from the measured position of the shower maximum Xmax - the depth in the atmosphere (in g/cm 2 )w here the number of ionizing particles reaches its maximal value. Not surprisingly, the observables used to determine the primary particle type - the lateral muon density ρμ and the EAS maximum position Xmax - appear to be very sensitive to details of high energy hadronic interactions. More precisely, Xmax depends strongly on the properties of the primary particle

Towards gamma-ray astronomy with timing arrays

The gamma-ray energy regime beyond 10 TeV is crucial for the search for the most energetic Galactic accelerators. The energy spectra of most known gamma-ray emitters only reach up to few 10s of TeV, with 80 TeV from the Crab Nebula being the highest energy so far observed significantly. Uncovering their spectral shape up to few 100 TeV could answer the question whether some of these objects are cosmic ray Pevatrons, i.e. Galactic PeV accelerators.Sensitive observations in this energy range and beyond require very large effective detector areas of several 10s to 100 square-km. While imaging air Cherenkov telescopes have proven to be the instruments of choice in the GeV to TeV energy range, very large area telescope arrays are limited by the number of required readout channels per instrumented square-km (due to the large number of channels per telescope). Alternatively, the shower-front sampling technique allows to instrument large effective areas and also naturally provides large viewing angles of the instrument. Solely measuring the shower front light density and timing (hence timing- arrays), the primary particle properties are reconstructed on the basis of the measured lateral density function and the shower front arrival times. This presentation gives an overview of the technique, its goals, and future perspective.

Roller compactor: The effect of mechanical properties of primary particles

In this study, the nano-indentation hardness of a single primary particle was measured for six different materials; microcrystalline cellulose, hydroxypropyl methylcellulose, maltodextrin, lactose, sodium carbonate and calcium carbonate. This was linked to the properties of the ribbons produced by roller compactor at different hydraulic pressures in the range of 30–230bar.The main investigated ribbon properties were strength, porosity and width. For the range of materials that were tested, it was found that the lower the nano-indentation hardness of the powder particles, the higher the strength, width and lower the ribbon porosity. This is because the applied pressure by the rollers was enough to plastically deform the particles and create bonds between them.A method was suggested to predict the workability of the powder in roller compactor by using the data of nano-indentation for three materials.

Macroporous polymer particles via reactive gelation under shear: effect of primary particle properties and operating parameters.

Reactive gelation under shear is a recently developed procedure toward rigid macroporous polymeric particles that does not require the use of any porogen. A comprehensive study of the effect of individual parameters on the resulting material characteristics is presented. Primary particle properties are found to be pivotal, namely, the primary particles size, cross-linking degree, and outer shell composition. Operating parameters also play a significant role; specifically, the effects of applied shear rate, salt feeding rate, swelling degree of primary particles, waiting time before postpolymerization, and postpolymerization temperature are investigated. By varying the operating conditions, the size, internal structure, as well as porosity of the fabricated microclusters may be controlled. The pores are invariably micrometer-sized, with pore size distributions exhibiting adjustable maxima. Thanks to the sequential character of the procedure, different parameters may be tuned individually at different stages along the preparation route, allowing thus for high versatility in the control of different properties of the final material.

Measurement and simulation of micromechanical properties of nanostructured aggregates via nanoindentation and DEM-simulation

During the production of nanoparticles in large scale processes, usually larger aggregates are synthesized and subsequently redispersed to obtain the desired product properties. Dispersion processes are energy intense and not always predictable or even unsuccessful. The resistance of aggregates against redispersion and thus, the micromechanical properties strongly depends on the aggregate structure and the primary particle properties as well as on the binding mechanisms. The aim of this study was the investigation of the deformation and breakage behavior of aggregated structures composed of nanoparticles. This was done by comparing experimental and computational results. The larger scale simulations were based on a dimensioning of interaction forces and geometry and calibrated using experimental nanoindentation results. As a result the nature and strength of particle–particle interactions can be described. Furthermore, the distribution of normal and radial forces within the aggregates was compared to theoretical models of aggregate breakage.

Chemical, Microphysical and Optical Properties of Primary Particles from the Combustion of Biomass Fuels

Biomass fuel combustion for residential energy significantly influences both emissions and the atmospheric burden of aerosols in world regions, i.e., east and south Asia. This study reports measurements of climate-relevant properties of particles emitted from biomass fuels widely used for cooking in south Asia, in laboratory experiments simulating actual cooking in the region. Fuel burn rates of 1-2 kg h(-1) for wood species, and 1.5-2 kg h(-1) for crop residues and dried cattle dung, influenced PM2.5 emission factors which were 1.7-2 g kg(-1) at low burn rates but 5-9 gkg(-1) at higher burn rates. Total carbon accounted for 45-55% and ions and trace elements for 2-12% of PM2.5 mass. The elemental carbon (EC) content was variable and highest (22-35%) in particles emitted from low burn rate combustion (wood and jute stalks) but significantly lower (2-4%) from high burn rate combustion (dried cattle dung and rice straw). The mass absorption cross-section (MAC, m2 g(-1)) correlated with EC content for strongly absorbing particles. Weakly absorbing particles, from straw and dung combustion, showed absorption that could not be explained by EC content alone. On average, the MAC of biofuel emission particles was significantly higher than reported measurements from forest fires but somewhat lower than those from diesel engines, indicating potential to significantly influence atmospheric absorption. Both for a given fuel and across different fuels, increased burn rates result in higher emission rates of PM2.5, larger organic carbon (OC) content, larger average particle sizes, and lower MAC. Larger mean particle size (0.42-1.31 microm MMAD) and organic carbon content, than in emissions from combustion sources like diesels, have potential implications for hygroscopic growth and cloud nucleation behavior of these aerosols. These measurements can be used to refine regional emission inventories and derive optical parametrizations, for climate modeling, representative of regions dominated by primary particles from biomass fuel combustion.

Suspension rheology during wet comminution in planetary ball mill

Obtaining and controlling desirable system behavior in terms of rheology is important issue in many engineering problems. This study monitors rheological behavior of dolomite suspensions produced by wet comminution in planetary ball mill. Dolomite has a number of uses, in agriculture, steel making, glass making, ceramic industry, pharmaceutical industry, etc. Therefore, it is very interesting for investigation. Rheological behavior of attained suspensions was characterized as strongly pseudoplastic whereas the pseudoplasticity degree was connected to particle size distribution. Rheological properties of the product become equal after the effective comminution time regardless of primary particle properties before comminution. Therefore, the comminution in a highly energetic mill such as planetary ball mill, within short time interval will induce development of systems with the same granulometric and consequently the same rheological properties regardless of the primary system properties before the comminution.

Kinetics of Aggregation and Gelation in Colloidal Dispersions

Control of aggregation and gelation of colloidal particles are among important issues in processing of disperse systems. We present an experimentally validated approach to kinetic modelling based on master curves for aggregation and gelation. The master curves depend on basic physicochemical properties of primary particles, which are reflected in terms of the cluster fractal dimension and kernel kinetic exponent. We also analyse interplay between aggregation and diffusion at small length scales in the process of formation of gel domains in imperfectly mixed colloidal dispersions.

Methods for Characterizing the Dustiness Estimation of Powders

The handling of powders, such as storing, conveying, filling, mixing etc. leads to airborne dust in the ambient air. These procedures almost represent a fault or a hazard, hence the capability of a powder to liberate dust is also a feature of quality. The amount of released dust of disperse particle systems depends on primary particle properties, such as particle size distribution, and also on the method and intensity of stressing. Also, quantitative description of dustiness always depends on the measuring method.

Retrostructural analysis of poly(vinyl chloride) particles

AbstractA poly(vinyl chloride) (PVC) matrix of final particles is investigated by means of quasi‐elastic light scattering (QELS) and high resolution porosimetry (HRP). It is demonstrated that the QELS method is a powerful tool for the detection of various higher organized structures in particle interiors, which in all likelihood will be a difficult‐to‐process fraction of the resin. Measurements of common PVC grades revealed that the QELS records are usually composed of three distinctly separated size distributions, which were assigned to the size distribution of single macromolecules dissolved (maximum at ca. 10 nm), associates of macromolecules (primary particles, the maximum at ca. 100–200 nm), and microglobules (the maximum at ca. 0.8–1 (μm)). The properties of primary particles are presented, as well as the correlation between QELS and HRP records. Based on this correlation, it can be suggested that the pore size distribution is in fact a morphological fingerprint of individual PVC resins. Some consequences of the results obtained for the evaluation of the processsing properties of PVC are discussed.

Particle characteristics and their influence on dewatering of kaolin, calcite and quartz suspensions

The effect of particle properties and dispersion on the filtration and dewatering behaviour of three different minerals namely kaolin, calcite and quartz in aqueous media have been examined. The primary particle properties such as particle size, size distribution, specific surface area, density, surface structure, dry bed porosities and sphericities of particles as well as their dispersion properties like solid concentration, pH and zeta potential have been considered. Quartz suspension shows higher settling rate and filterability (lower capillary suction time, CST) compared to calcite and kaolin at almost all solid concentrations and pH. The filterabilities of calcite and quartz are close to each other in the whole pH range and solid concentration. The settling and filterability of all three mineral suspensions showed dependence on slurry pH. The kaolin–water system showed strongest pH dependence in comparison to calcite and quartz–water system. Invariably, they all exhibited best settling and filterability characteristics at their respective point of zero charges (pzc). The vacuum filtration and dewatering characteristics of kaolin, calcite and quartz in aqueous suspensions in terms of cake permeability, specific resistance to filtration and cake saturation have been discussed on the basis of their particle size and its distribution, sphericity of the particles, bed porosity, water retaining capacities and the particle dispersion properties. Improved dewatering is observed near the pzc of each mineral.

Structural and textural study on ZrO 2-Y 2O 3 powders

Microporous gels of ZrO 2, ZrO 2·2mol% Y 2O 3 and ZrO 2·5mol%Y 2O 3 were treated in air and under vacuum at temperatures ranging from 450 to 1300 °C. X-ray and electron diffraction results seem to indicate that both, pure and doped zirconia gels crystallize in the cubic form of ZrO 2. On lengthening of the thermal treatment at 450 °C or after treatment at higher temperatures, the transformations cubic→tetragonal→monoclinic occur, but those are delayed as the yttria content in the sample increases. In some treatment conditions, cubic and tetragonal phases can also been retained to some extent in pure zirconia. Moreover, a rhombohedral deformation of the cubic cell along the 〈111〉 directions has been observed in some crystals of pure zirconia samples. Textural degradation takes place in both, pure and doped zirconia, due to particle growth and also the loss of porosity and therefore, the observed structural stabilization does not improve textural stability. The differences in the texture of pure and doped samples have been related to dehydration and crystal growth processes, and to the properties of primary particles in the gels.