Random Size Distribution Research Articles

Multi-Product Exporters: Verifying Stylized Facts

Abstract In this paper, we propose a statistical model to characterize the null hypothesis of the random product size distribution for multi-product exporters. It serves as a benchmark to test the empirical facts and model predictions. We ask which stylized facts that characterize multi-product exporters and motivate such theories as core competencies, productivity being a driver of both scope and scale, and economies of scope among others, are spurious, and which are informative. The benchmark model also provides alternative moments to test the validity of these theories.

Physical Unclonable Functions with Hyperspectral Imaging System for Ultrafast Storage and Authentication Enabled by Random Structural Color Domains.

Physical unclonable function (PUF) is attractive in modern encryption technologies. Addressing the disadvantage of slow data storage/authentication in optical PUF is paramount for practical applications but remains an on-going challenge. Here, a highly efficient PUF strategy based on random structural color domains (SCDs) of cellulose nanocrystal (CNC) is proposed for the first time, combing with hyperspectral imaging system (HIS) for ultrafast storage and authentication. By controlling the growth and fusion behavior of the tactoids of CNC, the SCDs display an irregular and random distribution of colors, shapes, sizes, and reflectance spectra, which grant unique and inherent fingerprint-like characteristics that are non-duplicated. Based on images and spectra, these fingerprint features are used to develop two sets of PUF key generation methods, which can be respectively authenticated at the user-end and the manufacturer-front-end that achieving a high coding capacity of at least 22304. Notably, the use of HIS greatly shortens the time of key reading and generation (≈5s for recording, 0.5-0.7s for authentication). This new optical PUF labels can not only solve slow data storage and complicated authentication in optical PUF, but also impulse the development of CNC in industrial applications by reducing color uniformity requirement.

Accumulation Dynamics of Defective Genomes during Experimental Evolution of Two Betacoronaviruses.

Virus-encoded replicases often generate aberrant RNA genomes, known as defective viral genomes (DVGs). When co-infected with a helper virus providing necessary proteins, DVGs can multiply and spread. While DVGs depend on the helper virus for propagation, they can in some cases disrupt infectious virus replication, impact immune responses, and affect viral persistence or evolution. Understanding the dynamics of DVGs alongside standard viral genomes during infection remains unclear. To address this, we conducted a long-term experimental evolution of two betacoronaviruses, the human coronavirus OC43 (HCoV-OC43) and the murine hepatitis virus (MHV), in cell culture at both high and low multiplicities of infection (MOI). We then performed RNA-seq at regular time intervals, reconstructed DVGs, and analyzed their accumulation dynamics. Our findings indicate that DVGs evolved to exhibit greater diversity and abundance, with deletions and insertions being the most common types. Notably, some high MOI deletions showed very limited temporary existence, while others became prevalent over time. We observed differences in DVG abundance between high and low MOI conditions in HCoV-OC43 samples. The size distribution of HCoV-OC43 genomes with deletions differed between high and low MOI passages. In low MOI lineages, short and long DVGs were the most common, with an additional cluster in high MOI lineages which became more prevalent along evolutionary time. MHV also showed variations in DVG size distribution at different MOI conditions, though they were less pronounced compared to HCoV-OC43, suggesting a more random distribution of DVG sizes. We identified hotspot regions for deletions that evolved at a high MOI, primarily within cistrons encoding structural and accessory proteins. In conclusion, our study illustrates the widespread formation of DVGs during betacoronavirus evolution, influenced by MOI and cell- and virus-specific factors.

Numerical study of TRISO particles with random size and location distribution in cuboid and cylindrical matrix: A validation for two-regime heat conduction model

During reactor operation, the precise size values or specific size distribution of tri-structural isotropic (TRISO) fuel particles randomly dispersed within the fully ceramic microencapsulated (FCM) fuel elements are often unknown. To investigate the impact of the random distribution of positions and sizes of TRISO particles within a cuboid or cylindrical matrix on the temperature distribution of fuel elements and to establish a practical heat conduction model, TRISO fuel particles with randomly distributed positions, diameters following Gaussian or uniform distributions are generated using relevant algorithms. A cuboid and a cylindrical TRISO fuel element are modeled in ANSYS, and a three-dimensional temperature field distribution of the fuel element is obtained through numerical simulation. The probability density of the maximum temperature of the fuel element is calculated and fitted. Finally, the applicability of the two-regime heat conduction model over a broader range is validated based on the simulated data. The conclusions of this study provide reference information for predicting the temperature distribution of FCM fuel elements containing TRISO particles with random size and location distribution.

An open-source robust machine learning platform for real-time detection and classification of 2D material flakes

The most widely used method for obtaining high-quality two-dimensional (2D) materials is through mechanical exfoliation of bulk crystals. Manual identification of suitable flakes from the resulting random distribution of crystal thicknesses and sizes on a substrate is a time-consuming, tedious task. Here, we present a platform for fully automated scanning, detection, and classification of 2D materials, the source code of which we make openly available. Our platform is designed to be accurate, reliable, fast, and versatile in integrating new materials, making it suitable for everyday laboratory work. The implementation allows fully automated scanning and analysis of wafers with an average inference time of 100 ms for images of 2.3 Mpixels. The developed detection algorithm is based on a combination of the flakes’ optical contrast toward the substrate and their geometric shape. We demonstrate that it is able to detect the majority of exfoliated flakes of various materials, with an average recall (AR50) between 67% and 89%. We also show that the algorithm can be trained with as few as five flakes of a given material, which we demonstrate for the examples of few-layer graphene, WSe2, MoSe2, CrI3, 1T-TaS2 and hexagonal BN. Our platform has been tested over a two-year period, during which more than 106 images of multiple different materials were acquired by over 30 individual researchers.

Phase and surface structures-optical transmittance correlation of sputtered Al-doped ZnO film on glass substrate

The electrical and optical properties of sputtered Al-doped ZnO films prepared on a glass substrate with different thicknesses (97, 127, 161, 211, and 276 nm) were systematically investigated. The 97 nm film showed only the main peak of the AZO (002) phase, whereas the rest films exhibited AZO (002) and (004) phases, and the peak intensities were obviously increased with increasing thickness. The films displayed a granular grain surface and columnar-like structure with different sizes and distributions depending on film thickness. Surface roughness was increased, whereas the electrical resistance was decreased with increasing film thickness. The smallest crystallite size of about 26 nm with the highest resistivity and lowest carrier concentration was observed on a 127 nm film, whereas the crystallite size of about 29 nm was observed on the 97, 161, 211, and 276 nm films. All AZO films exhibited good electrical properties and transparency with an averaged optical transmittance higher than 80% in the visible wavelength. The 162 nm film showed the highest transmittance of 86% in the wavelength range of 350–900 nm and a wide energy band gap of 3.52 eV because of the highest mobility and crystallite size with a columnar structure and random size distribution. The figure of merit (FOM) was strongly related to the optical band gap and tended to increase with increasing thickness. The results are attributed that the optical energy band gap was altered by film thickness by improving phase structure and surface morphology.

Effect of particle size on the dynamic properties of tire derived aggregates (TDA)

This paper investigates the dynamic properties of tire derived aggregate (TDA) as a recycled material used in civil engineering applications. The effect of TDA type A particle size on the dynamic response is studied experimentally in detail, and the effects of hysteresis loop asymmetry, shear strain, and confining pressure on the shear modulus and damping ratio are also examined. Undrained strain-controlled cyclic triaxial tests with consolidation stresses ranging from 25 to 200 kPa and shear strains ranging from 0.1 to 10% are used to compare a granulated rubber (GR) specimens and TDA specimens with different maximum particle sizes. The dynamic response of TDA type A differs from that of granulated rubber, because of the larger particle sizes of TDA type A. Although TDA stiffness increases with increasing particle size, the damping ratio is insensitive to TDA particle size in the particle size range considered in this study. However, at all consolidation stresses, the damping capacity of GR is significantly lower than that of TDA. In particular, due to hysteresis loop asymmetry, conventional equations can significantly underestimate the shear modulus and damping ratio of TDA type A. Furthermore, a generalized MKZ model is proposed to estimate the maximum shear modulus at small strains (Gmax) and to predict shear modulus degradation curves for TDA type A with maximum particle sizes ranging from 19.1 mm to 50.8 mm. Comparisons of these shear modulus degradation curves to data reported in the literature and to the experimental results of a TDA sample with a random particle size distribution show that the proposed generalized MKZ model can provide reasonable estimates of the shear modulus of TDA type A.

Stochastic modeling of blob-like plasma filaments in the scrape-off layer: Theoretical foundation

A stochastic model for a superposition of uncorrelated pulses with a random distribution of amplitudes, sizes, and velocities is presented. The pulses are assumed to move radially with fixed shape and amplitudes decaying exponentially in time due to linear damping. The pulse velocities are taken to be time-independent but randomly distributed. The implications of a distribution of pulse amplitudes, sizes, and velocities are investigated. Closed-form expressions for the cumulants and probability density functions for the process are derived in the case of exponential pulses and a discrete uniform distribution of pulse velocities. The results describe many features of the boundary region of magnetically confined plasmas, such as high average particle densities, broad and flat radial profiles, and intermittent large-amplitude fluctuations. The stochastic model elucidates how these phenomena are related to the statistical properties of blob-like structures. In particular, the presence of fast pulses generally leads to flattened far scrape-off layer profiles and enhanced intermittency, which amplifies plasma–wall interactions.

A Monte Carlo code for the collisional evolution of porous aggregates (CPA)

Context. The collisional evolution of submillimeter-sized porous dust aggregates is important in many astrophysical fields. Aims. We have developed a Monte Carlo code to study the processes of collision between mass-asymmetric, spherical, micron-sized porous silica aggregates that belong to a dust population. Methods. The Collision of Porous Aggregates (CPA) code simulates collision chains in a population of dust aggregates that have different sizes, masses, and porosities. We start from an initial distribution of granular aggregate sizes and assume some collision velocity distribution. In particular, for this study we used a random size distribution and a Maxwell-Boltzmann velocity distribution. A set of successive random collisions between pairs of aggregates form a single collision chain. The mass ratio, filling factor, and impact velocity influence the outcome of the collision between two aggregates. We averaged hundreds of thousands of independent collision chains to obtain the final, average distributions of aggregates. Results. We generated and studied four final distributions (F), for size (n), radius (R), porosity, and mass-porosity distributions, for a relatively low number of collisions. In general, there is a profuse generation of monomers and small clusters, with a distribution F (R) ∝ R−6 for small aggregates. Collisional growth of a few very large clusters is also observed. Collisions lead to a significant compaction of the dust population, as expected. Conclusions. The CPA code models the collisional evolution of a dust population and incorporates some novel features, such as the inclusion of mass-asymmetric aggregates (covering a wide range of aggregate radii), inter-granular friction, and the influence of porosity.

Voltammetric and spectroscopic studies of water/formamide ratios in the production of the cerium (III) hexacyanoferrate (II) nanoparticles

AbstractThe present study describes the simple and fast preparation of Cerium (III) hexacyanoferrate (II) (CeHCF) solid nanoparticles at three different water/formamide (%) ratios used as solvent (v/v) (100:0, 80:20, 0:100). CeHCF nanoparticles (Nps) were characterized by fourier transform infrared pectroscopy (FTIR), x‐ray diffraction (XRD), scanning electron microscopy (SEM), zeta potential and cyclic voltammetry (CV). Electrodes modified with CeHCF presented a well‐defined redox pair with formal potential (Eo′) of approximately 0.29 V (vs. Ag/AgCl(sat) attributed to the Fe2 +/Fe3+ redox pair in the presence of cerium (III)). The Nps in the three systems investigates, presents a random size distribution to different surface, where most were distributed between 20 and 160 nm. Considering the three investigated systems, only CeHCF‐1 (100:0) was sensitive to L‐dopamine, presenting a linear signal region as a function of L‐dopamine concentrations, with a limit of detection (LD) of 0.125 mmol L−1, limit of quantification (LQ) of 0.419 mmol L−1 and amperometric sensitivity (S) of 148.16 μA mmol L−1.

Models for resonant acoustic metasurfaces with application to moth wing ultrasound absorption.

Taking as bioinspiration the remarkable acoustic absorption properties of moth wings, we develop a simple analytical model that describes the interaction between acoustic pressure fields, and thin elastic plates incorporating resonant sub-structures. The moth wing is an exemplar of a natural acoustic metamaterial; the wings are deeply subwavelength in thickness at the frequencies of interest, the absorption is broadband and the tiny scales resonate on the moth wing acting in concert. The simplified model incorporates only the essential physics and the scales are idealized to flat rigid rectangular plates coupled via a spring to an elastic plate that forms the wing; all the components are deep-subwavelength at desired frequencies. Based on Fourier analysis, complemented by phenomenological modelling, our theory shows excellent agreement with simulation mimicking the moth-wing structure. Moth wings operate as broadband sound absorbers employing a range of scale sizes. We demonstrate that a random distribution of scale sizes generates a broadband absorption spectrum. To further illustrate the potential of the model, we design a deeply sub-wavelength acoustic counterpart of electromagnetically induced reflectance.This article is part of the theme issue ‘Wave generation and transmission in multi-scale complex media and structured metamaterials (part 2)’.

Structural and optical characteristics of nanoparticles of zinc oxide based ternary compounds generated by simple sol-gel technique.

A simple sol-gel process was employed to synthesize Zn1-xCdxO (x = 0, 0.02, 0.04, 0.06) nanoparticles. The powders have a Hexagonal Wurtzite phase, according to X-ray diffraction investigations. The findings of Rietveld refinement fitting revealed a considerable shift in the lattice parameters of Zn1-xCdxO compounds with increasing cadmium content. The average crystallite size of undoped ZnO, Zn0.98Cd0.02O, Zn0.96Cd0.04O, and Zn0.94Cd0.06O compounds was determined using Scherrer formula to be 41.58 nm, 38.05 nm, 37.92 nm, and 39.52 nm, respectively. SEM micrographs exhibit needle-like features in cadmium doped ZnO compounds, but not in undoped ZnO compounds. These micrographs also reveal that the nanostructures have a random size distribution and become more agglomerated as the cadmium concentration rises. The optical band gap, as determined by Ultraviolet-Visible Spectroscopy, decreased from 3.22 to 3.15 eV as cadmium content increased. The photoluminescence spectrum recorded at room temperature by 310 nm excitation wavelength. PL spectra exhibited three different emission bands around 410 nm, 460 nm and 510 nm. The broadness of strong green emission peak was observed to increase with cadmium concentration. All the luminescence peaks are explained as due to various defects like zinc vacancy, oxygen vacancy, zinc interstitial and their complexes.

A Dynamic Pore Network Model for Imbibition Simulation Considering Corner Film Flow

AbstractWetting films can develop in the corners of angular pores under strong wetting conditions. Modeling the dynamics of corner film remains elusive using direct numerical simulations because of the significant scale difference between main meniscus and corner film flow. In this paper, the modified interacting capillary bundle model (ICB), developed in our previous work to describe accurately corner film dynamics in a single square tube, is incorporated into a single‐pressure dynamic pore network model (DPNM) to simulate imbibition in strongly wetting porous media with corner film flow. The traditional pore network is decomposed into several layers of interacting subpore networks where the 0th layer of subpore network simulates the main meniscus flow and higher layers the corner film flow. The fluid flow between different layers is captured by interlayer throats. In addition, the snap‐off mechanism caused by the thickening of wetting corner film is considered. The accuracy of the developed model is validated for four cases: spontaneous imbibition in a single square tube, wetting fluid redistribution through corner films under a capillary pressure difference, snap off in a narrow throat connecting two large pores, and imbibition dynamics in a real microfluidic porous geometry. The validated model is then used to simulate both spontaneous and controlled imbibition in a pore network with random pore size distribution. The interaction between corner film and main meniscus flow in porous media is analyzed from a pore‐scale perspective.

Evaluation of the Structural Deviation of Cu/Cu2O Nanocomposite Using the X-ray Diffraction Analysis Methods

We successfully synthesized Cu/Cu2O nanocomposites using the wet chemical synthesis method. All X-ray diffraction (XRD), Reference Intensity Ratio (RIR), and Rietveld refinement methods confirmed that the compounds Cu and Cu2O are free of impurities. Scanning Electron Microscope (SEM) and Transmission electron microscopy (TEM) images show the morphology and interactions of Cu and Cu2O in the structure. The formation mechanism is also explained by five stages: precursor, nucleation, growth, aging, and reduction. The changes in crystallization parameters under variations in reaction temperature (Tv) and stirring speed (Sv) were confirmed by agreement with the XRD database. The lattice constant in the crystal of nanocomposite increases with rising temperature in the reaction, leading to unit cell expansion, while increasing the stirring—rate leads to a random size distribution of the lattice parameter. Due to the imperfect growth of the crystal, the induced crystallite size was calculated using the Williamson-Hall model, and the precise lattice parameter values were calculated using the Nelson-Riley function.

An insight into core flooding experiment via NMR imaging and numerical simulation

Traditional core flooding experiments can only be used post breakthrough while what happens in the core prior to this time is vital to understand multiphase flow phenomenon for more successful EOR operations. We can overcome this obstacle through a visualized fluid displacement scheme. This can ultimately provide us with a reliable relative permeability curve that can lead to a more accurate reservoir simulation outcome in the field scale. In this study, NMR imaging is employed in a water flood experiment in conjunction with two separate numerical two-phase flow simulation methods (FDM and FEM), to reproduce experimental data. Using the Brooks-Corey equation, random pore size distribution indices (λ) are selected to generate relative permeability curves. Moreover, simulations are performed with FDM, and oil displacement efficiency, saturation maps, and saturation profiles are generated and compared to the experimental results. Next, FEM was employed in COMSOL for further validation and FDM results were found in agreement with the experiments. This way, an appropriate relative permeability curve was generated and assigned to the sample. Results suggest that λ of 0.2 generated the best numerical results with an MSE value of 0.009 in oil displacement efficiency curves, comparable to the experiments. Collectively, integration of imaging techniques with routine experimental fluid displacement procedures presented a detailed insight into complicated nature of multiphase flow phenomena in geomaterials.

Pore Network Modeling to Study the Impacts of ‎Geometric Parameters on Water Transport inside Gas ‎Diffusion Layers

A pore network model (PNM) is proposed for the simulation of water transport inside the cathode side ‎gas diffusion layer (GDL) of polymer electrolyte fuel cells (PEFCs) during the transient start-up period as ‎well as the steady state. Numerous two-dimensional random networks representing GDL are generated ‎followed by statistical averaging of the results (Monte Carlo methods) to circumvent the uncertainties ‎imposed by random pore size distributions. The resulting liquid water saturation profiles within GDLs ‎exhibit concave patterns which is typically encountered in capillary fingering flow regimes in porous ‎media. The effect of GDL thickness and current collector rib width as two geometric parameters on water ‎transport dynamics are separately investigated. It turns out that thin and thick GDLs compared to the base ‎case can have contradicting outcomes on the account of total water saturation in the network. On the ‎other hand, wide current collector ribs give rise to liquid water saturation and build-up within GDL which ‎can lead to flooding. At the end, three-dimensional networks are generated demonstrating higher pore ‎connectivity which results in higher percolation times and different invasion patterns.‎

Wavelength and decay time tuning of intraband transitions in low spatial frequency laser-induced periodic surface structures

We present the study of the alteration of wavelength and decay time of intraband transitions in the laser-induced periodic surface structures (LIPSS) of silver formed by varying the incident laser peak fluence. The studies are performed using a femtosecond laser (λ0 = 800 nm) based ultrafast transient absorption spectroscopy (UFTS)setup. Using the same laser, an array (~2 mm size) of laser-induced periodic surface structures were obtained in a single-step fabrication process in the open air without translating the sample. Each unit cell of the array comprises low spatial frequency LIPSS (LSFL) near the center with nanoparticles/clusters around the edges. As obtained from 2D Fast Fourier Transform, the overall periodicity(Λ) of LSFL is within 0.714λ0–0.723λ0 range. The nanoparticles/clusters show a random size distribution that varies from 50 nm to 300 nm. In UFTS measurement, the LIPSS was excited by a 3.3 eV laser. The SPP/SPR dip in the data is an indication of intraband transition or hot electron generation. The effect of change in structuring due to varying laser fluence on these intraband transitions is also analyzed. It is observed that there is a non-linear redshift (~16 nm) in the SPR peak wavelength with a significant enhancement in the relaxation times of the hot electrons due to localized annealing of shallow defects. Therefore, a large tunability in wavelength of SPP/SPR and lifetime of hot electrons was achieved by varying the laser fluence. The study highlights the suitability of LIPSS in applications requiring efficient energy transfer, enhanced photocatalytic action, and tunable sensors.

Numerical method for predicting flow and segregation behaviors of fresh concrete

Current meshless particle methods are able to simulate the flow of fresh concrete, but fail to predict the segregation since fresh concrete is regarded as homogeneous fluid. This study aims to develop a numerical approach to predict the segregation of coarse aggregate (CA) in fresh concrete together with the flow behavior. A double-phase & multi-particle (DPMP) model was proposed to describe fresh concrete, which treats fresh concrete as a double-phase fluid composed of matrix mortar and the CA particles that had random shapes, size distribution, and different density from matrix mortar. Each CA particle was formed by the element particles, of which number was dependent on the size and shape of described CA particle. Three types of inter-particle interaction, including CA-CA particles, CA-mortar particles, and two mortar particles, were investigated, respectively. Then, based on the complete implicit MPS (I-MPS) method and the DPMP model, the L-box flow of two series of high fluidity concrete were simulated. The ability of the proposed numerical approach to simultaneously simulate the flow and segregation behaviors of fresh concrete was confirmed. Moreover, this numerical method can analyze the changes of localized rheological parameters of segregated concrete.

Year-round population dynamics of Limacina spp. early stages in a high-Arctic fjord (Adventfjorden, Svalbard)

The thecosome pteropods Limacina helicina and L. retroversa are important contributors to the zooplankton community in high-latitude environments but little is known about their distribution and life cycle under polar conditions. We collected the early life stages (< 1 mm) of the thecosome population in 2012 and 2013 at a bi-weekly to monthly resolution in fjord highly influenced by Arctic waters as well as Atlantic inflows (Adventfjorden, Svalbard, 78°N), together with environmental parameters. L. retroversa only occurred episodically, in association with the inflow of Atlantic water, with low numbers and random size distributions. This suggests that this boreal species does not fulfill its life cycle in Adventfjorden. In contrast, young specimens of L. helicina were present during the entire study. Veligers hatched in late summer/autumn and measured 0.14 mm on average. They grew with rates of 0.0006 mm day−1 over the 10–11 months of development. Only thereafter, growth accelerated by one order of magnitude and maximal rates were reached in autumn (0.0077 mm day−1). Our results indicate that L. helicina reaches a size of 1 mm after approximately 1.5 years in Adventfjorden. We therefore suggest that L. helicina overwinters the first year as a small juvenile and that it needs at least 2 years to reach an adult size of 5 mm in Adventfjorden. This reveals an complex and delicate aspect of the life-cycle of L. helicina and further research is needed to determine if it makes the population especially vulnerable towards climate changes.

Mesoscale study on the shock response and initiation behavior of Al-PTFE granular composites

A combination of mesoscale simulations and explosive loading experiments is used to investigate the shock response and shock-induced initiation behavior of aluminum-polytetrafluoroethylene (Al-PTFE) granular composites. A two-dimensional model following the random distribution of real Al particle sizes is developed and validated against experiments. The model is employed to investigate the effect of Al mass fractions on shock characterizes as well as Hugoniot relationships, and noticeable differences are visualized at the grain-level in the pressure, temperature, and strain response. Systematic shock structures in metals have been identified, and the underlying mechanisms of deformation and energy dissipation are discussed respectively. Results demonstrate that the high pressure is concentrated in the wave front, but a much greater heat and larger strain exhibit along grain/matrix interfaces that enable the friction dissipation the main mechanism of hot-spots formation. Specific quantities of critical temperature to initiate are obtained based on basic microstructure attributes to analyze the influence on hot-spots distribution by mass fractions. The interaction of shock wave with mesoscale heterogeneities accounts for the stochastic nature of the initiation process.