Gaussian Size Distribution Research Articles

Developing animal fat substitute in low-fat meatballs: A strategy to use high internal phase emulsions stabilized by Prinsepia utilis Royle protein

In promoting healthy diet, developing animal fat substitutes for meat products has been a prominent trend in food science. In this study, Prinsepia utilis Royle protein (PuRP) with amphiphilic property was extracted from waste oil pomace. High internal phase emulsions (HIPEs) were prepared with a 75% oil phase and stabilized with 2% (w/v) PuRP due to their excellent elastic-gel property. Furthermore, the PuRP-HIPEs were used to substitute animal fat in low-fat meatballs. Below 100 mM ionic strength, the uniformly distributed PuRP-HIPEs exhibited an approximate Gaussian size distribution with an average particle size of about 100 μm. The PuRP-HIPEs exhibited good thermodynamic stability and improved the texture of meatballs. Additionally, the PuRP-HIPEs significantly increased the mobile water content in steamed meatballs, resulting in better water retention and distribution than the free-fat and lard-added meatballs. Overall, the PuRP-HIPEs could substitute 100% animal fat in meatballs and maintain their cooking characteristics.

Simultaneous fluorination and carbonation to approach a high infrared transparent magnesium fluoride

In this research study, magnesium fluoride nanoparticles were successfully produced by the fluorination and carbonation method. MgF2 nanoparticles were calcined at temperature of 100, 300, 400, 500, 600, 640, and 680 °C. Also, polycrystalline magnesium fluoride ceramics were prepared using a hot-pressing process from calcined powders. The optical, structural, and mechanical characteristics of the magnesium fluoride samples were then investigated. The X-ray diffraction proved that magnesium fluoride nanoparticles were formed with a single-phase structure and no impurities. By using simultaneous fluorination and carbonation technique, crystalline MgF2 nanoparticles with a particle size of 50–60 nm were synthesized at a minimum temperature of 100 °C. Increasing the calcination temperature led to the evaporation of the volatile products and increased the crystallinity and particle size of MgF2 nano-particles. The optimal calcination temperature of 640 °C created a ceramic MgF2 with a hardness of 560 HV, and considerable relative density of 100%, and a high transmittance of over 90% in the 3.2–5.5 μm range. The obtained results, thus, revealed that the transparency of MgF2 ceramics was a function of the porosity and the grain size distribution. The microstructure of hot-pressed MgF2 confirmed a Gaussian grain size distribution in the range of 100–1000 nm, contributing to the enhancement of densification. An intra-granular fracture occurred in magnesium fluoride, which was related to the fine-grained structure of MgF2.

Multiphysics Modelling of Powder Coating of U-Profiles: Towards Simulation-based Optimization of Key-Performance Attributes by Variation of Powder-Parameters

Multiphysics simulation software has been developed to predict the key performance attributes of industrial powder coating applications based on applied process-parameter settings. The software is a Eulerian-Lagrangian finite-volume Multiphysics solver based on OpenFOAM, capable of modelling mass transfer effects between powder-coating pistols and electrically grounded metallic substrates. It considers various factors such as fluid dynamics of process airflow, coating-particle dynamics, particle-substrate interactions, and particle charging mechanisms within the corona. The software is fully compatible with Massive Simultaneous Cloud Computing technology, allowing hundreds of simulated coating scenarios to be computed simultaneously. Experimental validation efforts have been conducted, indicating a high degree of practical relevance of the technology.  The current simulation study aims to demonstrate the potential of the simulation software for adjusting coating lines and optimizing powder coating of U-profiles. Specifically, the study focuses on optimizing the key-performance-attributes of the powder coating application with respect to varying material parameters of the applied powder, namely mean particle diameter, standard deviation of Gaussian particle size distribution, and powder particle density. The software predicts and visualizes coating patterns, coating efficiencies, and the batch-based standard deviation of coating thickness on a U-shaped metallic substrate, resulting in concrete and optimized powder settings. The presented results and the applied software are highly relevant for powder material suppliers.&nbsp

Second-harmonic generation in polycrystalline ZnSe in the absence of phase matching

The work is devoted to the study of the second-harmonic generation (SHG) process as a result of random quasi-phase-matching of thulium laser radiation in ZnSe polycrystals. A linear dependence of the SHG efficiency on the nonlinear medium length has been observed in the experiment. The efficiencies of SHG in ZnSe polycrystals with average grain sizes from 35[Formula: see text][Formula: see text]m to 380[Formula: see text][Formula: see text]m were compared. The obtained results are in good agreement with the theory in the case of a Gaussian grain size distribution.

Significance of recirculating micro-bubbles in oxygenation from poly-dispersed plumes

Poly-disperse bubble plumes are simulated to explore the effect of interactions between multiple bubbles of varying sizes on the liquid flow, plume dynamics, and oxygen transfer in aeration processes. An Eulerian-Lagrangian model based on the multiphase particle-in-cell method (MPPIC) implemented in OpenFOAMTM has been extended to account for bubbly flow. Bubbles have been approximated as spherical particles whose diameters change in response to pressure and nitrogen and oxygen mass dissolution and transfer. The mass transfer model relies on a Sherwood number correlation which accounts for the individual bubble size and relative velocity and is parameterized against the liquid phase temperature. A Large Eddy Simulation (LES) approach based on a transport equation for the turbulent kinetic energy has been adopted to model the effect of the sub-grid scales (SGS) of turbulence on the liquid flow and bubble motion. The bubble injection is defined in terms of the air mass transfer and the bubble size distribution. The model has been compared against experimental measurements of the evolution in oxygen concentration in a 1m deep water tank in response to bubble plumes generated from a porous ceramic plates at two different flow rates. The interaction between milli- and micro-bubbles over a wide range of sizes has been shown to create significant differences in the aeration process. A method to correct for bubble recirculation has been proposed and allows for good agreement between measured and simulated volumetric transfer rates. The simulation has shown the important role that the interplay between bubble sizes takes in determining the oxygen transfer efficiency. Larger standard deviations from Gaussian bubble size distributions have been shown in particular to reduce recirculation from smaller bubbles thereby reducing the aeration efficiency at an equivalent flow rate. An analysis of the age distribution by bubble size plumes suggest that the largest bubble have an important role in increasing the entrainment of smaller bubbles limiting their recirculation and reducing their retention time.

Hard carbon microspheres with bimodal size distribution and hierarchical porosity via hydrothermal carbonization of trehalose.

Hydrothermal carbonization (HTC) is an efficient thermochemical method for the conversion of organic feedstock to carbonaceous solids. HTC of different saccharides is known to produce microspheres (MS) with mostly Gaussian size distribution, which are utilized as functional materials in various applications, both as pristine MS and as a precursor for hard carbon MS. Although the average size of the MS can be influenced by adjusting the process parameters, there is no reliable mechanism to affect their size distribution. Our results demonstrate that HTC of trehalose, in contrast to other saccharides, results in a distinctly bimodal sphere diameter distribution consisting of small spheres with diameters of (2.1 ± 0.2) μm and of large spheres with diameters of (10.4 ± 2.6) μm. Remarkably, after pyrolytic post-carbonization at 1000 °C the MS develop a multimodal pore size distribution with abundant macropores > 100 nm, mesopores > 10 nm and micropores < 2 nm, which were examined by small-angle X-ray scattering and visualized by charge-compensated helium ion microscopy. The bimodal size distribution and hierarchical porosity provide an extraordinary set of properties and potential variables for the tailored synthesis of hierarchical porous carbons, making trehalose-derived hard carbon MS a highly promising material for applications in catalysis, filtration, and energy storage devices.

A combined rate theory-population balance model of the evolution of irradiation-induced helium bubbles in metals during annealing

A multiscale model describing the evolution of helium bubbles in the irradiated materials is established based on the rate equations and the population balance equation. The size distribution of the helium bubbles and the evolution law of the statistical average size and number density of the bubbles with time changing predicted by the model are in good agreement with the experimental statistics. The influence of annealing temperature, annealing time, irradiation energy, irradiation flux, and coarsening mechanisms on the evolution of helium bubbles are numerically simulated and discussed, taking FeCrAl alloy as the irradiated material. The results show that the bubble evolution is dominated by the Ostwald ripening mechanism under high temperature annealing conditions (≥ 1073 K), and the time dependence of the average size and density of helium bubbles is consistent with the existing theoretical results. And the number of shrinking helium bubbles caused by Ostwald ripening is effectively reduced by the bubble coalescence effect, leading to further growth of the proportion of large-sized helium bubbles. Consequently, a Gaussian bubble size distribution has been obtained modeling the coupling of the Ostwald ripening mechanism and the bubble coalescence mechanism. The generation rates of helium and vacancy in the material during irradiation, as well as their ratio, are significant factors that can affect the nucleation and evolution of helium bubbles.

A multi-stage normalization model for predicting the porosity of the multi-sized mixtures

A multi-stage normalization (MSN) model is established to predict the porosity of the multi-sized mixture. Based on the random filling theory, the proposed model repeats binary packing and ternary packing to continuously normalize the particle size groups of the multi-sized mixture, and finally obtains the target porosity. The predictions by the MSN model are compared with the experimental data and the predictions from other models. The results show that the MSN model’s predictions are highly consistent with experimental data and correspond with the predictions given by the linear packing model, which demonstrates the validation of the MSN model. The MSN model can offer better predictions than the binary packing model, ternary packing model and empirical model due to a complete consideration of the particle size distribution. And the applicability of the model is further confirmed by investigating the porosity of mixtures with unimodal and bimodal Gaussian size distributions. • A multi-stage normalization model to predict multi-sized mixture porosity is built. • Porosities predicted by the MSN model and by other packing models are compared. • Porosities of mixtures with uni- and bi-modal Gaussian size distributions are studied.

K[formula omitted]K[formula omitted] and K[formula omitted]K± femtoscopy in pp collisions at [formula omitted] and 13 TeV

Femtoscopic correlations with the particle pair combinations KS0KS0 and KS0K± are studied in pp collisions at s=5.02 and 13 TeV by the ALICE experiment. At both energies, boson source parameters are extracted for both pair combinations, by fitting models based on Gaussian size distributions of the sources, to the measured two-particle correlation functions. The interaction model used for the KS0KS0 analysis includes quantum statistics and strong final-state interactions through the f0(980) and a0(980) resonances. The model used for the KS0K± analysis includes only the final-state interaction through the a0 resonance. Source parameters extracted in the present work are compared with published values from pp collisions at s=7 TeV and the different pair combinations are found to be consistent. From the observation that the strength of the KS0KS0 correlations is significantly greater than the strength of the KS0K± correlations, the new results are compatible with the a0 resonance being a tetraquark state of the form (q1,q2‾,s,s‾), where q1 and q2 are u or d quarks.

Syntheses, characterization, and suppression efficiency of silver & silver iodide nanoparticle for proliferation, migration, and invasion in follicular thyroid carcinoma cells

In this study, a chemical co-precipitation method has been employed, silver iodide (AgI NPs) and silver nanoparticles (AgNPs) have been synthesized. UV–vis, FTIR, x-ray diffraction, FESEM, TEM, and other techniques have been used to examine the optical and structural properties of AgNPs and AgI NPs. The UV–vis absorption spectra gave the highest peak at 400 nm for AgNPs and AgI NPs at 434 nm. The x-ray data showed that the prepared AgNPs and AgI NPs were nanocrystalline cubic structures with crystallite sizes of 18 nm and 51 nm, respectively. The FESEM results show that synthesized AgNPs and AgI NPs agglomerate and aggregate. TEM data revealed that AgNPs have a quasi-spherical shape and Gaussian size distribution type. TEM analysis of AgI NPs with different magnifications revealed primarily spherical and well dispersed AgI NPs. TEM histogram shows that the particles were highly monodispersed AgNPs and AgI NPs with an average diameter of 11.5, 24.28 nm, respectively. According to the MTT assay results of FTC133cells, the cytotoxic action IC50 of AgNPs was (52.74 μg ml−1) and for AgI nanoparticles was (95.22 μg ml−1). It has been found that FTC133 cellular uptake was concentration, size- and time-dependent for both AgNPs and AgI NPs. The migrated FTC133 cell rates were reduced following AgNPs treatment to 75.7% and for AgI NPs treatment to 60% compared with the control group. Furthermore, Invasive FTC133 cell rates were reduced by 60% in the AgNPs treatment group and by 55.71 percent in the AgI NPs treatment group compared to the control group.

Investigation of granular capillary rising under vertical vibration

The phenomenon of granular capillary rising under vertical vibration provides a novel technical route for hoisting, transporting and collecting granular materials. However, there are still obvious deficiencies in the existing studies of the granular capillary rising behavior, especially the intensive investigation on the effects of gravitational acceleration, horizontal vibration component and particle size distribution are still lacking. To address these problems, the discrete element method is used to numerically simulate the granular capillary rising phenomenon under different operating conditions. The final capillary rising height and average capillary rising velocity of the granular matter are computed and analyzed based on the numerical simulations. The results show that the granular capillarity can also occur under low gravity conditions, and that the final capillary rising height and the average capillary rising velocity first increase and then decrease with the gravitational acceleration. It is also found that the final capillary rising height is insensitive to the variation of horizontal vibrational component, whereas the average capillary rising velocity increases with the augmentation of horizontal vibrational component. Compared with the mono-sized particles, the particles with the same mean size but having a Gaussian size distribution exhibit a maximal capillary rising height at a larger critical tube diameter. Meanwhile, the average capillary rising velocity of the particles having a Gaussian size distribution is faster in the tube diameter range where the granular capillary dynamics for both size distributions is dominated by the jamming effect.

When Copper Oxide meets graphene oxide: A core-shell structure via an intermittent spray coating route for a highly efficient ammonium perchlorate thermal decomposition

Ammonium perchlorate (AP) is the primary oxygen source for solid propellants; its thermal decomposition behavior is determinant for the overall performance of the ensuing propellant. In this perspective, a novel Intermittent, Spray Coating, Draying, and Mixing (ISCDM) method is introduced herein to prepare AP@CuO, PA@GO, and AP@CuO@GO core-shell composites. The as-synthesized materials morphological information, crystalline structure, and elemental composition are probed by powder X-ray diffraction, Raman spectroscopy, energy-dispersive X-ray spectroscopy, and scanning electron microscopy. The as-prepared CuO nanospheres were effectively embedded into the AP microparticles surface. AP@CuO microparticles were continuously coated with graphene oxide (GO) nanosheets. Particle size analyzer was used to probe the particle size distribution of core-shell composites. Results show that the application of ISCDM method results in a typical narrow gaussian size distribution with an average diameter of hundred microns ranking from 158.56 µm to 166.22 µm. The thermal decomposition and the catalytic performances were investigated by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). AP@CuO@GO core-shell composite exhibits an excellent thermal decomposition behavior: a low thermal decomposition temperature (LTD) of 337 °C, reduced values of the High thermal decomposition temperature HTD to be overlapped with the LTD step, and a significant energy release of 1543 J g−1 are registered.

The Poissonian Origin of Power Laws in Solar Flare Waiting Time Distributions

Abstract In this study we aim for a deeper understanding of the power-law slope, α, of waiting time distributions. Statistically independent events with linear behavior can be characterized by binomial, Gaussian, exponential, or Poissonian size distribution functions. In contrast, physical processes with nonlinear behavior exhibit spatiotemporal coherence (or memory) and “fat tails” in their size distributions that fit power-law-like functions, as a consequence of the time variability of the mean event rate, as demonstrated by means of Bayesian block decomposition in the work of Wheatland et al. In this study we conduct numerical simulations of waiting time distributions N(τ) in a large parameter space for various (polynomial, sinusoidal, Gaussian) event rate functions λ(t), parameterized with an exponent p that expresses the degree of the polynomial function λ(t) ∝ t p . We derive an analytical exact solution of the waiting time distribution function in terms of the incomplete gamma function, which is similar to a Pareto type II function and has a power-law slope of α = 2 + 1/p, in the asymptotic limit of large waiting times. Numerically simulated random distributions reproduce this theoretical prediction accurately. Numerical simulations in the nonlinear regime (p ≥ 2) predict power-law slopes in the range of 2.0 ≤ α ≤ 2.5. The self-organized criticality model yields a prediction of α = 2. Observations of solar flares and coronal mass ejections (over at least a half solar cycle) are found in the range of α obs ≈ 2.1–2.4. Deviations from strict power-law functions are expected due to the variability of the flare event rate λ(t), and deviations from theoretically predicted slope values α occur due to the Poissonian weighting bias of power-law fits.

Effect of Gaussian size distribution width on minimum fluidization velocity in tapered gas–solid fluidized beds

This paper investigated the effect of Gaussian distribution width, average particle diameter, particle loading, and the tapered angle on minimum fluidization velocity (Umf) by conducting extensive experiments in tapered fluidized beds. Three powders with Gaussian size distribution and different distribution widths were used in the experiments. An increase in Umf with increasing the average particle diameter, particle loading, and the tapered angle was observed. There was also a nonmonotonic behavior of Umf as the Gaussian distribution width increased. An empirical correlation including dimensionless groups for predicting Umf in tapered beds was developed in which the effect of distribution width was considered. The proposed correlation predictions were in good agreement with the experimental data, with a maximum deviation of 16.5% and average and standard deviations of, respectively, 6.4% and 7.4%. The proposed correlation was also compared with three earlier models, and their accuracy was discussed.

Natural Rock Fractures: From Aperture to Fluid Flow

Fractures provide preferential flow paths and establish the internal “plumbing” of the rock mass. Fracture surface roughness and the matedness between surfaces combine to delineate the fracture geometric aperture. New and published measurements show the inherent relation between roughness wavelength and amplitude. In fact, data cluster along a power trend consistent with fractal topography. Synthetic fractal surfaces created using this power law, kinematic constraints and contact mechanics are used to explore the evolution of aperture size distribution during normal loading and shear displacement. Results show that increments in normal stress shift the Gaussian aperture size distribution toward smaller apertures. On the other hand, shear displacements do not affect the aperture size distribution of unmated fractures; however, the aperture mean and standard deviation increase with shear displacement in initially mated fractures. We demonstrate that the cubic law is locally valid when fracture roughness follows the observed power law and allows for efficient numerical analyses of transmissivity. Simulations show that flow trajectories redistribute and flow channeling becomes more pronounced with increasing normal stress. Shear displacement induces early aperture anisotropy in initially mated fractures as contact points detach transversely to the shear direction; however, anisotropy decreases as fractures become unmated after large shear displacements. Radial transmissivity measurements obtained using a torsional ring shear device and data gathered from the literature support the development of robust phenomenological models that satisfy asymptotic trends. A power function accurately captures the evolution of transmissivity with normal stress, while a logistic function represents changes with shear displacement. A complementary hydro-chemo-mechanical study shows that positive feedback during reactive fluid flow heightens channeling.

Effect of polydispersity on bubble characteristics of Geldart Group B particles

In order to enhance the understanding of the influences of bubble characteristics in bubbling fluidized beds of Gaussian and lognormal particle size distributions (PSDs) of Geldart Group B particles, machine learning tools were harnessed. The PSDs had the same Sauter-mean diameter and widths (i.e., ratio of standard deviation to Sauter-mean diameter) of between 10 and 30% and 10 – 70%, respectively. Self-organizing maps (SOMs) analysis of more than a thousand data rows each of Gaussian and lognormal PSD data indicate that bubble velocity, frequency, length, and probability are highly correlated. The optimal number of data assemblies that either the Gaussian or lognormal dataset can be divided into per the Calinski-Harabasz criterion was determined to be three, and it was found that the critical parameter that underlies the demarcation of the datasets was PSD width. This agrees with an earlier study on clusters, wherein the non-monodispersity of the particle systems was also responsible for the division of the dataset into distinct data assemblies. Furthermore, the number-based frequency of the particle species was better correlated with the bubbles than the mass-based one. The key highlight is the predominant influence of PSD width in demarcating the datasets into distinct data assemblies, which underscores the need to account for the polydispersity of particle systems and provides valuable insights towards model development.

Breakage of flawed particles by peridynamic simulations

In this paper, we use a 2D bond-based peridynamic model to investigate the strength of disk-shaped particles including pre-cracks. We use a diametral (or Brazilian) test to break the particles. For the flawless particles, we find that the stress distribution compares well with an analytical model accounting for the size of the contact zone, and the particle stiffness tends linearly to a well-defined value for increasingly resolved meshing. We then introduce cracks, which are numerically defined by reducing the Young modulus of the bonds crossing linear segments. We consider in detail the effect of a single vertical crack on the yield stress as a function of its position. We also consider a randomly distributed population of cracks with sizes generated from a Gaussian size distribution. For a parametric study with a hundred particles, we found a probability of failure that is well fit by a Weibull law. Finally, using an image analysis algorithm, we investigate the statistics of cracks and the resulting fragments.

Relaxation of the dielectric response in thin films of vanadium dioxide

The results of studying the processes of dielectric relaxation in thin nanocrystalline films of vanadium dioxide are presented. The existence of a non-Debye relaxation process was revealed, which is due to the presence of a distribution of relaxators over relaxation times according to the Cole-Davidson model. The activation energy of the dielectric relaxation process was found to be Ep = (0.9 ± 0.1) eV. The observed regularities are explained by a model which views the system as a set of relaxators whose physical parameters have different numerical values due to the Gaussian size distribution of nanocrystallites of the VO2 film. The temperature change in the parameters of the dielectric relaxation process, detected at T = 340 K, indicates that a complex Mott-Peierls semiconductor-metal phase transition occurs at a given temperature in the VO2 nanocrystalline film.

Mineral snowflakes on exoplanets and brown dwarfs

Context. Exoplanet atmosphere characterisation has become an important tool in understanding exoplanet formation, evolution, and it also is a window into potential habitability. However, clouds remain a key challenge for characterisation: upcoming space telescopes (e.g. the James Webb Space Telescope, JWST, and the Atmospheric Remote-sensing Infrared Exoplanet Large-survey) and ground-based high-resolution spectrographs (e.g. the next-generation CRyogenic high-resolution InfraRed Echelle Spectrograph) will produce data requiring detailed understanding of cloud formation and cloud effects for a variety of exoplanets and brown dwarfs. Aims. We aim to understand how the micro-porosity of cloud particles affects the cloud structure, particle size, and material composition on exoplanets and brown dwarfs. We further examine the spectroscopic effects of micro-porous particles, the particle size distribution, and non-spherical cloud particles. Methods. We expanded our kinetic non-equilibrium cloud formation model to study the effect of micro-porosity on the cloud structure using prescribed 1D (Tgas–pgas) profiles from the DRIFT-PHOENIX model atmosphere grid. We applied the effective medium theory and the Mie theory to model the spectroscopic properties of cloud particles with micro-porosity and a derived particle size distribution. In addition, we used a statistical distribution of hollow spheres to represent the effects of non-spherical cloud particles. Results. Highly micro-porous cloud particles (90% vacuum) have a larger surface area, enabling efficient bulk growth higher in the atmosphere than for compact particles. Increases in single scattering albedo and cross-sectional area for these mineral snowflakes cause the cloud deck to become optically thin only at a wavelength of ~100 μm instead of at the ~20 μm for compact cloud particles. A significant enhancement in albedo is also seen when cloud particles occur with a locally changing Gaussian size distribution. Non-spherical particles increase the opacity of silicate spectral features, which further increases the wavelength at which the clouds become optically thin. Conclusions. Retrievals of cloud properties, particularly particle size and mass of clouds, are biased by the assumption of compact spherical particles. The JWST mid-infrared instrument will be sensitive to signatures of micro-porous and non-spherical cloud particles based on the wavelength at which clouds are optically thin. Details of spectral features are also dependent on particle shape, and greater care must be taken in modelling clouds as observational data improves.

Random loose packings of polydisperse adhesive microparticles with Gaussian size distribution

We perform a systematical numerical study on the random packings of polydisperse adhesive microspheres by means of a 3D discrete element method with adhesive contact mechanics. Empirical equations on the prediction of both bulk packing density and mean coordination number are proposed, which only depend on the normalized size variance, and an adhesion number decided by the mean particle size. On the basis of the geometrical navigation map tessellation, unique local size-topology relations for polydisperse particle system are discovered, which do not rely on the size variance. Apart from that, the radial distribution function, the angular distribution function and the distribution of surface-to-surface distance are employed to characterize the structural properties of the obtained packings. The analysis shows that the radial distribution function and the angular distribution function are not well-defined functions for multi-size particle system as the typical structural features are flattened due to the increase of size polydispersity. On the other hand, the distribution of surface-to-surface distance could be a suitable alternative for characterizing packing structures of polydisperse microparticles.