Experimental determination of mean particle sizes in an aerosol.
Aerosol mean particle size determined by rapid approximate method based on Mie light scattering theory
PARTICLE SIZE↗
SEARCH · Engineering Papers
Results for “Particle methods”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The signature of parallel electric fields in a collisionless plasma
The presence of a parallel electric field in the magnetosphere should be apparent through its effect on particles. An analysis is made of particle trajectories in phase space for a steady state collisionless plasma. The analysis utilizes the concepts of distribution function, total energy, and magnetic moment because all three quantities are conserved in a steady state situation in the absence of collisions. Two methods are presented for using particle data to gain information on the potential distribution. The first method involves the use of measurements of both ion and electron distribution functions and invokes the principle of quasi-neutrality. The second method involves the observation of discontinuities in velocity space which can be interpreted in terms of the effect of the electric field on the apparent loss or source cone.
Whipple, E. C., Jr.↗
Wave-wave interactions due to scattering by electrons.
The kinetic wave equation which describes the nonlinear wave-particle interaction in a plasma is considered, and a method which uses the picture of quantized plasmons interacting with particles for the description of nonlinear wave-particle interactions is briefly described. In this method an assumption is made of the Markoffian character of the equation. It is shown that the Markoffian assumption can be justified at least for the case when the plasma is close to a stable stationary state. The diagram method developed by Nishikawa (1966) is used to derive an explicit expression for the kinetic equation. The application of the result to the case of interaction between an electron-wave and an ion-wave is discussed.
Nishikawa, K.↗
Effects of ion trapping and fluctuations of electron temperature and plasma flow on cross-beam energy transfer
The influences of ion trapping and fluctuations of electron temperature and plasma flow on cross-beam energy transfer (CBET) are examined using two- and three-dimensional particle-in-cell simulations in parameter regimes relevant to recent CBET experiments at the OMEGA laser facility. In mid-Z plasma irradiated by an intense pump beam and weaker probe beam, ion trapping, collisional de-trapping, and plasma flow induced by thermal effects are shown to affect the CBET gain. Ion trapping can enhance or detune the CBET resonance [Nguyen et al., Phys. Plasmas 28, 082705 (2021)]. Collisional de-trapping can affect the CBET gain at low seed beam intensity near the onset threshold for ion trapping. Thermal-effects-induced flow can also detune the CBET resonance at a level comparable to that from trapping at low seed beam intensity. As a consequence, the CBET gain is sensitive to collisions and dimensionality at low seed beam intensity where ion trapping is weak but is insensitive to collisions and dimensionality at high seed beam intensity where ion trapping is strong.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Utilizing the maximum likelihood estimator for flow analysis
We explore the possibility of evaluating flow harmonics by employing the maximum likelihood estimator (MLE). For a given finite multiplicity, the MLE simultaneously furnishes estimations for all the parameters of the underlying distribution function while efficiently suppressing the variance of measures. Also, the method provides a means to assess a specific class of mixed harmonics, which is not straightforwardly feasible by the approaches primarily based on particle correlations. The results are analyzed using the Wald, likelihood ratio, and score tests of hypotheses. Besides, the resultant flow harmonics obtained using MLE are compared with those derived using particle correlations and event plane methods. Here, the dependencies of extracted flow harmonics on the multiplicity of individual events and the total number of events are analyzed. It is shown that the proposed approach works efficiently to deal with the deficiency in detector acceptability. Moreover, we elaborate on a fictitious scenario where the event plane is not a well-defined quantity in the distribution function. For the latter case, the MLE is shown to largely perform better than the two-particle correlation estimator. In this regard, one concludes that the MLE furnishes a meaningful alternative to the existing approaches for flow analysis.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Photon topology
The topology of photons in vacuum is interesting because there are no photons with k = 0, creating a hole in momentum space. We show that while the set of all photons forms a trivial vector bundle $γ$ over this momentum space, the R and L photons form topologically nontrivial subbundles $γ±$ with first Chern numbers ∓2. In contrast, $γ$ has no linearly polarized subbundles, and there is no Chern number associated with linear polarizations. It is a known difficulty that the standard version of Wigner’s little group method produces singular representations of the Poincaré group for massless particles. By considering representations of the Poincaré group on vector bundles we obtain a version of Wigner’s little group method for massless particles which avoids these singularities. Here we show that any massless bundle representation of the Poincaré group can be canonically decomposed into irreducible bundle representations labeled by helicity, which in turn can be associated to smooth irreducible Hilbert space representations. This proves that the R and L photons are globally well defined as particles and that the photon wave function can be uniquely split into R and L components. This formalism offers a method of quantizing the electromagnetic field without invoking discontinuous polarization vectors as in the traditional scheme. We also demonstrate that the spin-Chern number of photons is not a purely topological quantity. Lastly, there has been an extended debate on whether photon angular momentum can be split into spin and orbital parts. Our work explains the precise issues that prevent this splitting. Photons do not admit a spin operator; instead, the angular momentum associated with photons’ internal degree of freedom is described by a helicity-induced subalgebra corresponding to the translational symmetry of $γ$.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Magnetic fly-ash geopolymer for heavy metal removal in aqueous solutions
Novel magnetic geopolymers were manufactured by synthesizing magnetic Fe 3 O 4 particles on the surface of prepared geopolymer (Method 1) or by incorporating pre-synthesized magnetic Fe 3 O 4 particles into the geopolymer during the manufacture of the geopolymer (Method 2). This study evaluated the effect of the incorporated magnetic Fe 3 O 4 on the geopolymer magnetic, physical, and adsorption properties and its separation in aqueous solutions. Based on several preliminary measurements on the synthesized magnetic geopolymers, Method 2 was found to be a better method for producing magnetic geopolymer. Magnetic geopolymer synthesized by Method 2 exhibited ferromagnetic properties comparable to that of magnetic Fe 3 O 4 , with a saturation magnetization of 8 emu·g −1 and an intrinsic coercivity of 265 Oe. The magnetic geopolymer was efficiently separated from an aqueous solution within 2 min using a 0.48-T magnetic field. In addition, the magnetic geopolymer has a maximum copper adsorption capacity of 111.1 mg·g −1 , which was similar to the non-magnetic reference geopolymer indicating that the addition of magnetic Fe 3 O 4 did not compromise the geopolymer adsorption capacity. The magnetic geopolymer is a promising material with good adsorption and separation properties that can be used for heavy metals removal and recovery in wastewater and metals separation in industrial processes.
fly ash↗
Enhanced Detection of Primary Biological Aerosol Particles Using Machine Learning and Single-Particle Measurement
Accurately identifying primary biological aerosol particles (PBAPs) using analytical techniques poses inherent challenges due to their resemblance to other atmospheric carbonaceous particles. Here, we present a study of an enhanced method for detecting PBAPs by combining single-particle measurement with advanced supervised machine learning (SML) techniques. We analyzed ambient particles from a variety of environments and lab-generated standards, focusing on chemical composition for traditional rule-based and clustering approaches and incorporating morphological features into the SML approaches, neural networks and XGBoost, for improved accuracy. This study demonstrates that SML methods outperform traditional methods in quantifying PBAPs, achieving significant improvements in precision, recall, F1-score, and accuracy, leading to an increased number of detected PBAPs by at least 19%. The adaptability of the proposed XGBoost-based SML model is showcased in comparison to traditional methods in categorizing PBAPs for blind data sets from different geographical locations. Two field case studies were investigated, over agricultural land and Amazonia rain forest, representing relatively low and high concentrations of PBAPs, respectively, where XGBoost consistently detected up to 3.5 times more PBAPs than traditional methods. Precise detection of PBAPs in the atmosphere could significantly improve the prediction of climatic impacts by them.
42 ENGINEERING↗
Energetic decomposition yields efficient bimetallic Cu MOF-derived catalysts
Metal–organic frameworks (MOFs) have recently emerged as efficient self-sacrificial templates to fabricate porous carbon-supported metal nanoparticles (NPs). Due to observed increased activity, catalysts containing bimetallic NPs represent an active frontier for heterogeneous catalyst development. A strategy to synthesize active catalysts with highly dispersed bimetallic metal/metal oxides within a porous carbon matrix via rapid MOF decomposition using dopants is presented in this paper. A 2,4,6-trinitrotoluene (TNT) additive enhances the rapid thermolysis of the metal-doped Cu-based MOFs to minimize particle aggregation. Catalyst characterization reveals that a secondary metal increases dispersion of both metals over the carbon composite support. The catalyst preparation method influences both the metal particle size and oxidation state. Catalytic performance shows increased rates for 4-nitrophenol reduction even with <1 wt% of added secondary metal. Among the synthesized catalysts, the Ni–CuO@C bimetallic catalyst exhibits outstanding activity. This synthetic strategy is useful for creating highly efficient, robust, non-noble metal catalysts for development of sustainable chemical processes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A high level Ab initio study of the anionic hydrogen-bonded complexes FH-CN-, FH-NC-, H2O-CN- and H2O-NC-
HF, H2O, CN- and their hydrogen-bonded complexes were studied using state-of-the-art ab initio quantum mechanical methods. A large Gaussian one particle basis set consisting of triple zeta plus double polarization plus diffuse s and p functions (TZ2P + diffuse) was used. The theoretical methods employed include self consistent field, second order Moller-Plesset perturbation theory, singles and doubles configuration interaction theory and the singles and doubles coupled cluster approach. The FH-CN- and FH-NC- and H2O-CN-, H2O-NC- pairs of complexes are found to be essentially isoenergetic. The first pair of complexes are predicted to be bound by approx. 24 kcal/mole and the latter pair bound by approximately 15 kcal/mole. The ab initio binding energies are in good agreement with the experimental values. The two being shorter than the analogous C-N hydrogen bond. The infrared (IR) spectra of the two pairs of complexes are also very similar, though a severe perturbation of the potential energy surface by proton exchange means that the accurate prediction of the band center of the most intense IR mode requires a high level of electronic structure theory as well as a complete treatment of anharmonic effects. The bonding of anionic hydrogen-bonded complexes is discussed and contrasted with that of neutral hydrogen-bonded complexes.
Lee, Timothy J.↗
A high-level ab initio study of the anionic hydrogen-bonded complexes FH-CN(-), FH-NC(-), H2O-CN(-), and H2O-NC(-)
HF, H2O, CN- and their hydrogen-bonded complexes were studied using state-of-the-art ab initio quantum mechanical methods. A large Gaussian one particle basis set consisting of triple zeta plus double polarization plus diffuse s and p functions (TZ2P + diffuse) was used. The theoretical methods employed include self consistent field, second order Moller-Plesset perturbation theory, singles and doubles configuration interaction theory and the singles and doubles coupled cluster approach. The FH-CN- and FH-NC- and H2O-CN-, H2O-NC- pairs of complexes are found to be essentially isoenergetic. The first pair of complexes are predicted to be bound by approx. 24 kcal/mole and the latter pair bound by approximately 15 kcal/mole. The ab initio binding energies are in good agreement with the experimental values. The two being shorter than the analogous C-N hydrogen bond. The infrared (IR) spectra of the two pairs of complexes are also very similar, though a severe perturbation of the potential energy surface by proton exchange means that the accurate prediction of the band center of the most intense IR mode requires a high level of electronic structure theory as well as a complete treatment of anharmonic effects. The bonding of anionic hydrogen-bonded complexes is discussed and contrasted with that of neutral hydrogen-bonded complexes.
Lee, Timothy J.↗
Monte Carlo simulation of the passage of $\gamma$-rays and $\alpha$-particles in CsI
In this work, theoretical and computational methods for simulating the creation of ionization tracks by fast ions in solids were applied to the passage of a-particles in CsI, an inorganic scintillator commonly used for radiation detection. The methods were implemented in a Monte Carlo program to simulate the interaction of $\alpha$-particles, with incident energies of up to 1 MeV, with CsI. The simulations followed the fate of individual electron-hole pairs and thus allowed for a detailed description of the microscopic structure of ionization tracks created by incident radiation. Simulations were also performed with $\gamma$-rays of the same energy to compare and contrast the ionization tracks obtained with both types of particle. Intrinsic properties such as the mean energy per electron-hole pair, Fano factor, maximum theoretical light yield, and spatial distributions of electron-hole pairs were computed for both $\alpha$-particles and $\gamma$-rays. $\alpha$-particles created cylindrical tracks that were initially aligned with the incident direction and with initial radii of a few nanometers, whereas $\gamma$-rays showed significant scattering, resulting in probability distributions with lower intensities and much greater radial extents.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Correlations of azimuthal anisotropy Fourier harmonics with subevent cumulants in p Pb collisions at s N N = 8.16 TeV
Event-by-event long-range correlations of azimuthal anisotropy Fourier coefficients ($v_n$) in 8.16 TeV p Pb data, collected by the CMS experiment at the CERN Large Hadron Collider, are extracted using a subevent four-particle cumulant technique applied to very low multiplicity events. Each combination of four charged particles is selected from either two, three, or four distinct subevent regions of a pseudorapidity range from -2.4 to 2.4 of the CMS tracker, and with transverse momentum between 0.3 and 3.0 GeV. Using the subevent cumulant technique, correlations between $v_n$ of different orders are measured as functions of particle multiplicity and compared to the standard cumulant method without subevents over a wide event multiplicity range. At high multiplicities, the $v_2$ and $v_3$ coefficients exhibit an anticorrelation; this behavior is observed consistently using various methods. The $v_2$ and $v_4$ correlation strength is found to depend on the number of subevents used in the calculation. As the event multiplicity decreases, the results from different subevent methods diverge because of different contributions of noncollective or few-particle correlations. Correlations extracted with the four-subevent method exhibit a tendency to diminish monotonically toward the lowest multiplicity region (about 20 charged tracks) investigated. These findings extend previous studies to a significantly lower event multiplicity range and establish the evidence for the onset of long-range collective multiparticle correlations in small system collisions.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Adaptive autoencoder latent space tuning for more robust machine learning beyond the training set for six-dimensional phase space diagnostics of a time-varying ultrafast electron-diffraction compact accelerator
In this work, we present a general adaptive latent space tuning approach for improving the robustness of machine learning tools with respect to time variation and distribution shift. We demonstrate our approach by developing an encoder-decoder convolutional neural network-based virtual 6D phase space diagnostic of charged particle beams in the HiRES ultrafast electron diffraction (UED) compact particle accelerator with uncertainty quantification. Our method utilizes model-independent adaptive feedback to tune a low dimensional 2D latent space representation of ~1 million dimensional objects which are the 15 unique 2D projections (x, y),...,(z, p z ) of the 6D phase space (x, y, z, p x , p y , p z ) of the charged particle beams. We demonstrate our method with numerical studies of short electron bunches utilizing experimentally measured UED input beam distributions.
43 PARTICLE ACCELERATORS↗
Particle analysis in an acoustic cytometer
The present invention provides systems and methods for using acoustic radiation pressure to fractionate particles within a fluid.
Kaduchak, Gregory↗
Conditional deep generative models for simultaneous simulation and reconstruction of entire events
We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.
Dreyer, Etienne [Weizmann Institute of Science, Re↗
Numerical Investigation of Enhanced Dehumidification Processes By Using Dielectrophoresis Principles in Moist Airflows
Dispersed particle-laden flows are encountered in many building and industrial applications, such as flow in a fluidized bed, hydrocarbon transportation in pipelines, and the fouling of air-cooled heat exchangers (Kuruneru et al., 2016; Ray et al., 2019; Wang et al., 2019). Computational fluid dynamic (CFD) models have been developed in recent years to depict particle-fluid and particle-particle interactions in laminar or turbulent flows with increasing accuracy and stability. One particular particle-laden system of interest for moisture control is electrically-enhanced condensation in air and water droplet flows. Electrically-enhanced condensation consists of the use of highly charged water droplets injected in the moist air. The droplets become electric seeds that attract polar water vapor molecules to their surfaces and promote condensation. The nucleation and growth of the charged droplets deplete the vapor phase near a droplet, which is compensated for by the dielectrophoresis flow and diffusion. Dielectrophoresis flow involves surrounding vapor at a distance of about 10 to 100 nm for droplets charged by an electrospray compared to ~2 nm for a single electron charge in a droplet. As the vapor molecules collapse on the surface of the droplets, their initial electrical charge decreases with time due to the neutralization of the ions. While the physics of this phenomena is well known, engineering models for predicting the condensation rates are not available. This work computationally investigates dehumidification of moist airflow in a converging rectangular duct. The objective is to develop an engineering model that predicts water vapor condensation by employing dielectrophoresis principles. We construct a Computational Fluid Dynamics (CFD) model of the duct with electrically-enhanced condensation. The model is implemented in the open-source software OpenFOAM. We utilize the Multi-Phase Particle-In-Cell (MP-PIC) method coupled with a Population Balance Equation (PBE) approach to simulate the particle-laden system. This methodology is an Eulerian-Lagrangian approach used to simulate the droplets' behavior in the humid air. The MP-PIC approach (Andrews and O'Rourke, 1996) mitigates the computational cost by parceling several fundamental particles with similar properties (such as types, sizes, and temperature) into one computational particle. Thus, the billions of particles can be substituted by millions of computational particles without significant loss of information. The PBE was considered with the Lagrangian frame to combine the particle distribution function used in MP-PIC (Kim et al., 2020). This approach preserves mass and energy conservation between the phases in the Eulerian and Lagrangian structures. The PBE in this procedure was directly linked to the discrete parcels, making the simulation of the particle distribution computationally efficient and robust. The MP-PIC-PBE approach used in the present work was applied to the dehumidification of air. Water droplets were injected in the air stream and forced to grow according to experimentally derived correlation. The experiments were conducted on a converging duct with the same geometry and boundary conditions used to build the CFD model. This approach enabled us to approximate the effect of dielectrophoresis phenomena on the droplet and air interface. This presentation will discuss the details of the new CFD model built for the duct, the implementation of the model in OpenFOAM CFD programming language, and the experimental validation of the newly developed model. The results revealed a moderate yet measurable increase in droplet diameter due to water vapor condensation at the vapor-liquid interface of the electrically charged droplets' surface. The seed water droplet particles grew in size by capturing the water vapor in the surrounding air. The OpenFOAM model predicted reductions of humidity in the air from 5 to 10 percent.
Yel Mahi, Maliha↗
Precipitating Condensation Clouds in Substellar Atmospheres
We present a method to calculate vertical profiles of particle size distributions in condensation clouds of giant planets and brown dwarfs. The method assumes a balance between turbulent diffusion and precipitation in horizontally uniform cloud decks. Calculations for the Jovian ammonia cloud are compared with previous methods. An adjustable parameter describing the efficiency of precipitation allows the new model to span the range of predictions from previous models. Calculations for the Jovian ammonia cloud are found to be consistent with observational constraints. Example calculations are provided for water, silicate, and iron clouds on brown dwarfs and on a cool extrasolar giant planet.
Ackerman, Andrew S.↗