Experimental investigation of the effect of inlet particle properties on the capture efficiency in an exhaust particulate filter
Not Available
Viswanathan, Sandeep↗
SEARCH · Engineering Papers
Results for “PARTICLE PROPERTIES”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Evaluation of two-particle properties within finite-temperature self-consistent one-particle Green’s function methods: Theory and application to GW and GF2
One-particle Green’s function methods can model molecular and solid spectra at zero or non-zero temperatures. One-particle Green’s functions directly provide electronic energies and one-particle properties, such as dipole moment. However, the evaluation of two-particle properties, such as $\langle$S 2 $\rangle$ and $\langle$N 2 $\rangle$, can be challenging because they require a solution of the computationally expensive Bethe–Salpeter equation to find two-particle Green’s functions. We demonstrate that the solution of the Bethe–Salpeter equation can be completely avoided. Applying the thermodynamic Hellmann–Feynman theorem to self-consistent one-particle Green’s function methods, we derive expressions for two-particle density matrices in a general case and provide explicit expressions for GF2 and GW methods. Such density matrices can be decomposed into an antisymmetrized product of correlated one-electron density matrices and the two-particle electronic cumulant of the density matrix. Cumulant expressions reveal a deviation from ensemble representability for GW, explaining its known deficiencies. We analyze the temperature dependence of $\langle$S 2 $\rangle$ and $\langle$N 2 $\rangle$ for a set of small closed-shell systems. Interestingly, both GF2 and GW show a non-zero spin contamination and a non-zero fluctuation of the number of particles for closed-shell systems at the zero-temperature limit.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Triple-Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme
In the original Predicted Particle Properties (P3) bulk microphysics scheme, all ice-phase hydrometeors are represented by one or more “free” ice categories, where the physical properties evolve smoothly through changes to the four prognostic variables (per category), and with a two-moment representation of the particle size distribution. As such, the spectral dispersion cannot evolve independently, which thus results in limitations in representation of ice—in particular, hail—due to necessary constraints in the scheme to prevent excessive gravitational size sorting. To overcome this, P3 has been modified to include a three-moment representation of the size distribution of each ice category through the addition of a fifth prognostic variable, the sixth moment of the size distribution. The details of the three-moment ice parameterization in P3 are provided. The behavior of the modified scheme, with the single-ice-category configuration, is illustrated through simulations in a simple 1D kinematic model framework as well as with near large-eddy-resolving (250-m grid spacing) 3D simulations of a hail-producing supercell. It is shown that the three-moment ice configuration controls size sorting in a physically based way and leads to an improved capacity to simulate large, heavily rimed ice (hail), including mean and maximum sizes and reflectivity, and thus an overall improvement in the representation of ice-phase particles in the P3 scheme.
54 ENVIRONMENTAL SCIENCES↗
Propagation of statistical uncertainties in covariant density functional theory: Ground state observables and single-particle properties
Statistical errors in ground state observables and single-particle properties of spherical even-even nuclei and their propagation to the limits of nuclear landscape have been investigated in covariant density functional theory (CDFT) for the first time. Here, we consider only covariant energy density functionals with non-linear density dependency. Statistical errors for binding energies and neutron skins significantly increase on approaching two-neutron drip line. On the contrary, such a trend does not exist for statistical errors in charge radii and two-neutron separation energies. The absolute and relative energies of the single-particle states in the vicinity of the Fermi level are characterized by low statistical errors ($\sigma(e_i)\sim 0.1$ MeV). Statistical errors in the predictions of spin-orbit splittings are rather small. Statistical errors in physical observables are substantially smaller than related systematic uncertainties. As a result, at the present level of the development of theory, theoretical uncertainties at nuclear limits are dominated by systematic ones. Statistical errors in the description of physical observables related to the ground state and single-particle degrees of freedom are typically substantially lower in CDFT as compared with Skyrme density functional theory. The correlations between the model parameters are studied in detail. The parametric correlations are especially pronounced for the $g_2$ and $g_3$ parameters which are responsible for the density dependence of the model. The accounting of this fact potentially allows to reduce the number of free parameters of non-linear meson coupling model from six to five.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
EPCAPE – Ultrafine Particle Properties Field Campaign Report
The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Eastern Pacific Cloud Aerosol Precipitation Experiment – Ultrafine Particle Properties (EPCAPE-UPP) campaign combined a unique suite of instruments to probe the chemical and physical properties of ultrafine (sub-100-nm) atmospheric particles from 15 April to 15 June 2023 at the Mt. Soledad campaign site near San Diego, California.
54 ENVIRONMENTAL SCIENCES↗
Effects of the particle properties on electrochemical performance of nanocrystalline LiAl 0.1 Cu 0.1 Mn 1.8 O 4 cathode materials prepared by ultrasonic spray pyrolysis
LiAl 0.1 Cu 0.1 Mn 1.8 O 4 particles were prepared by the ultrasonic spray pyrolysis using nitrate salts at 800 °C in air atmosphere. The effects of ultrasonic frequency (120 kHz and 2.4 MHz) of the atomizer on the particle properties were investigated by X-ray diffraction, scanning and transmission electron microscopy, and energy dispersive spectroscopy. In addition, cyclic voltammetry and galvanostatic tests were performed to study the influence of the particle structure on the electrochemical behavior in Li-ion battery half-cell. Particle characterization studies reveal that the LiAl 0.1 Cu 0.1 Mn 1.8 O 4 particles have a nanocrystalline spinel structure. The secondary particles have a spherical morphology and the average particle size of the samples decreases with increase in frequency from 3.5 μm to 770 nm. Both samples have porous and partly hollow structure. The initial discharge capacities of LiAl 0.1 Cu 0.1 Mn 1.8 O 4 particles produced using 120 kHz and 2.4 MHz atomizers are 82 and 75 mAh·g -1 , respectively, between 3.0 and 4.8 V at 0.1C rate. Discharge capacities at the 4 V potential region drop to 85% of the initial values for both samples after 110 cycles. Although the micron-sized LiAl 0.1 Cu 0.1 Mn 1.8 O 4 particles exhibit higher capacity at 0.1C than the finer particles, the cathode prepared from the submicron particles has a better rate capability with a retention of the discharge capacity that is 3 times higher at 4C rate.
36 MATERIALS SCIENCE↗
Improvements in Global Climate Model Microphysics Using a Consistent Representation of Ice Particle Properties
This paper describes a new approach for representing ice microphysics in climate models. In contrast with most previous schemes, this approach does not include separate categories for cloud and precipitating ice and instead uses a single two-moment category to represent all solid hydrometeors. Thus, there is no need for an ice “autoconversion” size threshold parameter, which has a critical impact on simulated climate in the Community Atmosphere Model (CAM5) yet is poorly constrained by theory or observations. Further, in the new treatment, all ice microphysical processes and parameters, including ice effective radius and mean fall speed, are formulated self-consistently and flexibly based on empirical ice particle mass–size and projected area–size relationships. This means that the scheme can represent the physical coupling between bulk particle density, mean fall speed, and effective radius, which is not possible in current schemes. Two different methods for specifying these relationships based on observations are proposed. The new scheme is tested in global simulations using CAM5. Differences in simulations using the two methods for specifying the mass– and projected area–size relationships, particularly the cloud radiative forcing, are attributable mainly to the effects on mean ice particle fall speed, impacting sedimentation and ice water path. With some tuning of parameters involved in calculating homogeneous freezing it produces a similar climate compared to the simulations using the original CAM5 microphysics. Thus, it can produce a comparable climate while improving the physical basis and self-consistency of ice particle properties and parameters.
54 ENVIRONMENTAL SCIENCES↗
Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging
Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.
54 ENVIRONMENTAL SCIENCES↗
Single-particle properties of N = 12 to N = 20 silicon isotopes within the dispersive optical model
Experimental neutron and proton single-particle energies in N = 12 to N = 20 silicon isotopes and data on neutron and proton scattering by nuclei of the isotope {sup 28}Si are analyzed on the basis of the dispersive optical model. Good agreement with available experimental data was attained. The occupation probabilities calculated for the single-particle states in question suggest a parallel-type filling of the 1d and 2s{sub 1/2} neutron states in the isotopes {sup 26,28,30,32,34}Si. The single-particle spectra being considered are indicative of the closure of the Z = 14 proton subshell in the isotopes {sup 30,32,34}Si and the N = 20 neutron shell.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Synthesis of UO 2 nanoparticles via coulometric titration: influence of electrolytes and ligands on synthesized particle properties
Here, this study investigates the controlled synthesis of uranium oxide nanoparticles (UO 2 NPs) via coulometric titration under ambient conditions, focusing on the impact of electrolyte anions, salt concentrations, and strongly complexing ligands on particle formation and properties. Using dilute solutions of mineral acids (HNO 3 , HCl, and HClO 4 ), we demonstrate that the choice of electrolyte anion affects particle size, polydispersity, and surface charge. Particle characterization using dynamic light scattering and transmission electron microscopy shows that particles synthesized in perchlorate are largest and show a high degree of polydispersity. In comparison, particles synthesized in chloride are smaller and more uniform in size. Synthesis in nitrate yields a wide variety of particle sizes, with the major fraction (>65 %) having a smaller size than that obtained in the other two electrolytes. The presence of more strongly coordinating ligands such as sulfate and acetate modulate hydrolysis and condensation reactions, with sulfate suppressing nanoparticle formation across a wide concentration range ([SO 4 2- ] > 5 mM) and acetate enabling stable colloidal suspensions at [HOAc] ≤ 0.1 M. Synthesis in concentrated electrolytes (2 M NaNO 3 , NaCl, or NaClO 4 ) accelerates reaction kinetics but introduces challenges, as particles showed increased polydispersity and aggregation, and were more prone to oxidation. Electrolyte effects on actinide oxide nanoparticle formation are discussed and a short comparison to established nanoparticle syntheses is drawn. This work underscores the importance of tailoring synthesis parameters to achieve desired nanoparticle properties, providing valuable insights for optimizing UO 2 NP production for various applications.
Actinide hydrolysis↗
Observations of high-time-resolution and size-resolved aerosol chemical composition and microphysics in the central Arctic: implications for climate-relevant particle properties
Abstract. Aerosols play a critical role in the Arctic's radiative balance, influencing solar radiation and cloud formation. Limited observations in the central Arctic leave gaps in understanding aerosol dynamics year-round, affecting model predictions of climate-relevant aerosol properties. Here, we present the first annual high-time-resolution observations of submicron aerosol chemical composition in the central Arctic during the Arctic Ocean 2018 (AO2018) and the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expeditions. Seasonal variations in the aerosol mass concentrations and chemical composition in the central Arctic were found to be driven by typical Arctic seasonal regimes and resemble those of pan-Arctic land-based stations. Organic aerosols dominated the pristine summer, while anthropogenic sulfate prevailed in autumn and spring under haze conditions. Ammonium, which impacts aerosol acidity, was consistently less abundant, relative to sulfate, in the central Arctic compared to lower latitudes of the Arctic. Cyclonic (storm) activity was found to have a significant influence on aerosol variability by enhancing emissions from local sources and the transport of remote aerosol. Local wind-generated particles contributed up to 80 % (20 %) of the cloud condensation nuclei population in autumn (spring). While the analysis presented herein provides the current central Arctic aerosol baseline, which will serve to improve climate model predictions in the region, it also underscores the importance of integrating short-timescale processes, such as seasonal wind-driven aerosol sources from blowing snow and open leads/ocean in model simulations. This is particularly important, given the decline in mid-latitude anthropogenic emissions and the increase in local ones.
Heutte, Benjamin (ORCID:0000000173727460)↗
The effects of surface and particle properties on adhesion in humid environments using the enhanced centrifuge method
Not Available
Stevenson, Caralyn A.↗
Parametric Analysis of Particle CSP System Performance and Cost to Intrinsic Particle Properties and Operating Conditions.
Abstract not provided.
Albrecht, Kevin↗
Rapid Evaluation of Particle Properties using Inverse SEM Simulations
This report is the final deliverable of a 3 year project whose purpose was to investigate the possibility of using simulations of X-ray spectra generated inside a scanning electron microscope (SEM) as a means to perform quantitative analysis of the sample imaged in the SEM via an inverse analysis methodology. Using the nine point Technology Readiness Levels (TRL) typically used by the US Department of Defense (DOD) and the National Aeronautics and Space Administration (NASA), this concept is now at a TRL of 3. In other words, this work has proven the feasibility of this concept and is ready to be further investigated to address some of the issues highlighted by this initial proof of concept.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Rapid evaluation of particle properties using inverse SEM simulations
The characteristic X-rays produced by the interactions of the electron beam with the sample in a scanning electron microscope (SEM) are usually captured with a variable-energy detector, a process termed energy dispersive spectrometry (EDS). The purpose of this work is to exploit inverse simulations of SEM-EDS spectra to enable rapid determination of sample properties, particularly elemental composition. This is accomplished using penORNL, a modified version of PENELOPE, and a modified version of the traditional Levenberg Marquardt nonlinear optimization algorithm, which together is referred to as MOZAIK-SEM. The overall conclusion of this work is that MOZAIK-SEM is a promising method for performing inverse analysis of X-ray spectra generated within a SEM. As this methodology exists now, MOZAIK-SEM has been shown to calculate the elemental composition of an unknown sample within a few percent of the actual composition.
Bekar, Kursat B↗
Polarization as a Tool for Studying Particle Properties
Explore the source record for details and available documents.
Grosse-Wiesmann, P.↗
Characterizing the Effect of Particle Properties and Surface Topography Towards Overall Powder Adhesion Through the Enhanced Centrifuge Method.
Abstract not provided.
Stevenson, Caralyn↗
Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework
Ice microphysics parameterizations in models must make major simplifications relative to observations, typically employing empirical relationships to represent average functional properties of particles. However, previous studies have established that ice particle properties vary even in similar cloud types and thermodynamic environments, and it remains unclear how this so-called “natural variability” impacts simulated deep convection. This uncertainty is addressed by implementing a stochastic framework into the Predicted Particle Properties microphysics scheme in the Weather Research and Forecasting model. The approach stochastically varies the coefficients of the mass-size (m-D) relationship (m=aD b ) for unrimed and partially rimed ice. Using guidance from aircraft in situ measurements obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), the scheme samples from distributions of the prefactor (a) and the exponent (b) of the m-D relationship. Simulations of two MC3E deep convective cases indicate that the stochastic m-D scheme produces considerable variability of anvil cirrus cloud optical depth (τ) distributions, even for the same ice water path (IWP). Thus, the stochastic scheme produces variable cloud radiative forcing that is independent of IWP. This τ-IWP relationship variability is nonexistent using the deterministic m-D ensemble. Additional sensitivity tests are performed in which the fallspeed-size relationship (V=cD d ) is stochastically varied, resulting in variable precipitation amounts and rain rate distributions. Results are presented in the context of satellite and precipitation observations and include comparison with other ensemble configurations using perturbed initial and lateral boundary conditions and small-amplitude noise added to the potential temperature field.
54 ENVIRONMENTAL SCIENCES↗