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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Particle signal considerations for isotope ratio analysis with single particle multi-collector inductively coupled plasma mass spectrometry

Particle analysis has benefitted from the advent of single particle inductively coupled plasma-mass spectrometry (spICP-MS) due to its robustness, sensitivity, and high-throughput nature. Previous methods of spICP-MS have typically utilized quadrupole or time-of-flight mass analyzers and therefore employ electron multiplier-based detectors (such as secondary electron multipliers or microchannel plates). However, to obtain precise measurements on elemental or isotopic ratios within individual particles, multi-collector ICP-MS (MC-ICP-MS) can be used. Here, we investigate Ce isotope ratios, specifically 142 Ce/ 140 Ce, by spMC-ICP-MS using an all-Faraday cup collector array. Using 1 μm (diameter) cerium dioxide particles, integration times of the Faraday cup detectors were varied from 50–500 ms. The signal from the cerium isotopes in the particles was used to determine isotope ratios, which closely matched the expected natural isotopic abundances. Due to the signal decay response from the Faraday cups, the signal from particles lasts much longer than the expected 1–2 ms (up to 100 s of ms). To explore this effect on isotope ratio analysis, multiple ratio analysis methods were used to determine how to obtain optimal precision and accuracy. Relative differences were around 2% for methods that calculated isotope ratios from summing the total signal of an individual particle before calculating the ratio (rather than using every data point individually). It was found that summing all data points per particle, or integrating under the signal peak, yielded both accurate and precise isotope ratios within the particle population. Particles were also sampled off a solid substrate via microextraction, and isotope ratios were determined with relative differences of 0.13% to 9%. This demonstrates the ability to use spMC-ICP-MS to obtain isotope ratios on particles, with little to no relative difference in comparison to the expected ratio, even when operating Faraday detectors at fast 50 ms integration times.

Szakas, Sarah E. [Oak Ridge National Laboratory (O↗
DOE OSTI2022

On analysis and stochastic modeling of the particle kinetic energy equation in particle-laden isotropic turbulent flows

In this study, we analyze three-dimensional particle-laden, isotropic turbulence to develop an understanding of inertial particle dynamics from a kinetic energy perspective. Data trends implying inhomogeneous sampling of the flow by particles are identified and used to support a proposed particle behavior: particles appear to accumulate in regions of low flow kinetic energy over time because they lose kinetic energy and slow down in such regions, ultimately causing them to spend more time there. To elucidate this behavior, we derive a particle kinetic energy equation from the particle momentum equation, which incorporates inertial effects through the Schiller–Naumann drag correlation. Upon extracting fundamental physics from this equation, hypotheses regarding the role of the Stokes number in the temporal change of particle kinetic energy and the previously proposed particle behavior are evaluated using simulation data considering three Stokes numbers. Finally, a Fokker–Planck equation is used to derive the steady-state probability density function of the particle kinetic energy. The model fits the simulation data well and provides a tool for further investigation into understanding preferential concentration, as well as a reduced order model for predicting particle kinetic energy in turbulent flows.

42 ENGINEERING↗
DOE OSTI2021

Bimodal particle distributions with increased thermal conductivity for solid particles as heat transfer media and storage materials

Solid particles are being considered in several high temperature thermal energy storage systems and as heat transfer media in a variety of advanced power generation systems, particularly in concentrated solar power plants. The downside of such an approach is the low overall heat transfer coefficients caused by the inherently low thermal conductivity values of the low-cost solid media when coupled to heat exchanger for the power cycle working fluid. Choosing the right particle size distribution, emittance, and material of the solid media can all make a substantial difference in packed bed thermal conductivity. Current research though exclusively focuses on continuous unimodal distributions of particles. Here, in this work, we propose the use of a binary particle system with a bimodal size distribution to significantly increase packed bed thermal conductivity by reducing packed bed porosity. This is the first study related to ceramic solid particle heat transfer that has considered the thermal conductivity of non-unimodal size distributions at room and elevated temperatures. The following study found that for the binary particle system using Carbo particles CP 16/30 – CP 70/140 where the large particle volume fraction was 50% there was an 17–47% increase in packed bed thermal conductivity when compared with a nearly unimodal particle size distribution of CP 16/30 between 50 and 300 °C. Two different porosity and effective thermal conductivity models were studied, with one providing better prediction of porosity but both effective thermal conductivity models providing less predictive capacity. Importantly this approach can have a substantial impact of thermal performance, with little to no impact on the particle cost.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol

Particle phase state is a property of atmospheric aerosols that has important implications for the formation, evolution, and gas/particle partitioning of secondary organic aerosol (SOA). In this work, we use a size-resolved chemistry and microphysics model (SOM-TOMAS), updated to include an explicit treatment of particle phase state, to constrain the bulk diffusion coefficient (Db) of SOA produced from ??- pinene ozonolysis. By leveraging data from laboratory experiments performed in the absence of a seed and under dry conditions, we find that the Db for SOA can be constrained (1-7 ×10-15 cm2 s-1 in these experiments) by simultaneously reproducing the time-varying SOA mass concentrations and the evolution of the particle size distribution. Another version of our model that used the predicted SOA composition to calculate the glass transition temperature, viscosity, and, ultimately, Db (~10-15 cm2 s-1) of the SOA was able to reproduce the mass and size distribution measurements when we included oligomer formation (oligomers accounted for about a fifth of the SOA mass). Our work highlights the potential of a size resolved SOA model to constrain the particle phase state of SOA by utilizing historical measurements of the evolution of the particle size distribution.

He, Yicong↗
DOE OSTI2022

Deep learning for drag force modelling in dilute, poly-dispersed particle-laden flows with irregular-shaped particles

Here, this study applies machine learning-based approaches to develop a drag force model for irregular-shaped particles in incompressible flows. The particle-laden flows are studied through an in-house particle-resolved direct numerical simulation (PR-DNS) at low-intermediate Reynolds numbers (Re). We utilize the PR-DNS to obtain drag force coefficients and flow fields of single particles. A variational auto-encoder model is used to obtain latent vectors to represent the geometrical features of the particles, and artificial neural networks (ANN) are developed to predict drag force coefficients and flow fields of the single particles. This study applies a pairwise interaction extended point-particle (PIEP) model to obtain the coefficients assuming the flow fields of neighboring particles can be linearly superposed. The PIEP method shows significant improvement on prediction for a few neighbored particles. In addition, the results reveal R2 scores of 0.56-0.62 and errors of 9.1-10.0 % for the dilute, polydispersed systems with a volume fraction of 0.5 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Three-Dimensional Evaluation of Sand Particle Fracture Using Discrete-Element Method and Synchrotron Microcomputed Tomography Images

Recent research showed that fracture of sand particles plays a significant role in determining the plastic bulk volumetric changes of granular materials under different loading conditions. One of the major tools used to better understand the influence of particle fracture on the behavior of granular materials is discrete-element modeling (DEM). This paper employed the bonded block model (BBM) to simulate the fracture behavior of sand. Each sand particle is modeled as an agglomerate of rigid blocks bonded at their contacts using the linear-parallel contact model, which can transmit both moment and force. DEM simulated particles closely matched the actual three-dimensional (3D) shape of sand particles acquired using high-resolution 3D synchrotron microcomputed tomography (SMT). Results from unconfined one-dimensional (1D) compression of a single synthetic silica cube were used to calibrate the model parameters. Particle fracture was investigated for specimens composed of three sand particles that were loaded under confined 1D compression. Breakage energy measured from DEM models matched well with that measured experimentally. The paper studied the effects of contact loading condition and particle interaction on the fracture mode of particles using BBM that can closely capture the 3D shape of real sand particles.

58 GEOSCIENCES↗
DOE OSTI2021

Particle velocity measurement within a free-falling particle curtain using microscopic shadow velocimetry

We report an optical method for particle velocity measurement that is suitable for the measurement of particle velocities within dense particle-laden flows with high spatial resolution. The technique is based on particle shadow velocimetry with the use of a long-distance microscopic lens for images collection. The narrow depth of field of the lens allows particles within the focal plane to have much higher pattern intensities than those outside it on the collected images. Data processing was then employed to remove particles from outside the focal plane based on the gradient of the signal and a threshold. Following this, particle velocity was calculated from two successive images in the usual way. The technique was successfully demonstrated in a free-falling particle curtain with volume fractions in the four-way coupling regime of near-spherical micro-particles falling under gravity. The method was successfully employed to measure the transverse velocity profile through the curtain, which is the first time that such a measurement has been performed. Other highly-fidelity experimental data, which is also well suited to model development and validation, include the particle mass flow rate, curtain thickness and opacity.

Han, Shipu (ORCID:0000000278545882)↗
DOE OSTI2022

Advanced Physics Models for Particle-Particle Interactions (UCD final report)

The LDRD "Advanced Physics Models for Particle-Particle Interactions” collaborative research with Professor Jennifer Sinclair Curtis and PhD student Chanh Nguyen at the University of California, Davis involved meso-scale, discrete element method (DEM) modeling of micron-sized particles impacting a substrate. Using DEM, physical insight into the details of particle response upon impact can be obtained. Such details provide the type of information necessary to enhance existing continuum or macro-scale simulation tools so that modeling for material strength and particle breakage models is based on particle physics versus empirical relationships. While molecular dynamics simulations of atoms can also provide physical insight into the particle response to impact, the scale of particles that are treated is on the order of angstroms, not microns. This study gives evidence to the ability of the DEM simulation technique to provide such fundamental, detailed insight for micron-sized particles as a function of particle properties and impact velocity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Impact of particle size and particle-flow-wall coupling on pressurized oxy-combustion in the down-fired burner

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the burner of a pressurized oxy-combustor is close or even higher than the maximum limit that commercial CFD codes (e.g., ANSYS FLUENT) can handle. At this high particle volume fraction, the interactions among particles, fluid flow, and wall need to be re-evaluated. The present computational work is the first step of a systematic analysis of the particle influence, like releasing method, releasing locating, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing ANSYS FLUENT, using Reynolds-averaged Navier-Stokes (RANS) modeling. It is revealed that for this pilot-scale, pressurized burner, velocity profiles of the near-wall region in this POC facility exhibit some discrepancy against the near-wall turbulent flow velocity profile. In order to investigate the particle influence in the near-wall region, particle releasing location will be investigated. Numerical simulation results exhibit the coupling effect of turbulence flow and particles in this case. The particle size also demonstrates a great effect on particle trajectory, then further has an impact on flame stability and temperature.

Li, Lei↗
DOE OSTI2024

Large eddy simulation of particle dispersion analysis in a pressurized reactive fluid–particle system

Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new combustion technologies. Because of high pressure, the volumetric fraction of particles in a pressurized oxy-combustor could be higher than that in the conventional combustor, consequently, the particle dynamics in the pressurized vessel need to be evaluated accordingly. Specifically, the present computational work analyzes the pattern of the particle dispersion by extracting the particle mass flow rate and the particle size distribution in the pressurized combustor. A large eddy simulation (LES) with the environment pressure 15-bar and 100 kWth thermal input of fuel particle has been performed. The particle mass flow rates sampled in several cross-section planes strongly fluctuate, indicating the impacts of the flame as well as the gas-phase flow on the particle movement. Animations of the particle-gas flow show that the flow recirculation plays a major role in producing the pulsing phenomenon of the particle mass flow rate.

Li, Lei↗
DOE OSTI2026

Lead Isotope Fingerprinting of Nanoscale Mineral Particles via Single Particle Inductively Coupled Plasma Mass Spectrometry

Determining lead (Pb) isotopic ratios is of broad interest across chemical disciplines for source tracing and age determinations, but the technique is inherently limited when multiple sources of Pb are present in a single sample. Single particle methods offer a solution to directly resolve multiple distinct isotopic ratios within individual samples. In this study, single particle inductively coupled plasma-mass spectrometry (spICP-MS) was performed using time-of-flight (TOF) and multicollector (MC)-based platforms to measure the Pb isotopic composition of individual nanoscale particles. Distinct Pb isotope ratios were measured in particles from four powdered galena samples of different origins (average single-particle 206Pb/207Pb ratios ranging from 0.91 to 1.28) using both the TOF and the MC-based platforms. Differentiation of galena particles in a mixture (liberated grains and those hosted in a silicate matrix) was possible due to detecting their unique multielemental fingerprints. The differing behavior of the two galena samples during digestion was investigated; undigested galena particles trapped within silicate minerals were detected using spICP-MS, which has implications for Pb recovery in bulk-scale isotopic analysis. The multinuclide detection capability of the ICP-TOF-MS instrument allowed for the simultaneous detection of secondary constituent elements within the nanoparticles and the identification of multiple populations of isotopically distinct Pb-bearing particles in a copper ore sample, whereas the increased sensitivity of the MC instrument enabled quantification of 204Pb, allowing differentiation using multiple isotopic ratios. A single particle isotope ratio analysis module was developed within an open-source spICP-TOF-MS data processing platform, enabling its adoption across chemical disciplines.

Goodman, Aaron J. [University of Montreal, Quebec,↗
DOE OSTI2021

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↗
DOE OSTI2021

Droplet and Particle Methods to Investigate Turbulent Particle Laden Jets

The SARS-CoV-2 pandemic has heightened the interest in particle-laden turbulent jets generated by breathing, talking, coughing and sneezing, and how these can contribute to disease transmission. We present quantitative measurement methods for such flows, while exploring and offering improvements for common shortcomings. We generate jets consisting of either liquid droplets or solid particles in an isothermal, quiescent and electrically isopotential experimental chamber that was constructed to control the effects of ambient forcing on jet behavior. For liquid droplets, we find promise in surface deposition analysis based on fluorescent tracer use. For particles, we explore the performance of commercially available adhesive sampling strips and develop conductive grounded carbon tape based sampling strips. We explore ways in which the smallest of thermal gradients or electrostatic charge issues can affect particle dispersion, and suggest practical methods to address these issues. The developed methods are applied to study the simultaneous deposition of (Formula presented.) 25, 50 and 200 μm solid particles from a particle laden turbulent jet with a mean velocity of 33.2 m/s. The deposition location as a function of particle size was compared to results from a simple numerical RANS model, and illustrates ways in which imprecise initial or boundary conditions can lead to a notable deviation from experimental results. The differences in deposition pattern seen in experimental and numerical results despite a carefully controlled environment and characterized particle ejection indicate the need for a more stringent numerical model validation, especially when studying fate and transport of mid-range (neither purely aerosol or ballistic) sized particles.

42 ENGINEERING↗
DOE OSTI2026

Spectro-Microscopic Analysis of Soot Particle Composition and Source Attribution

Ambient soot particles significantly impact Earth’s radiative balance, human health, and atmospheric visibility. Their microstructural properties depend on formation and aging mechanisms, which vary by emission source and atmospheric processes. Hence, accurately identifying sources of soot enhances our understanding of their physicochemical properties and atmospheric implications. This study used a multi-modal approach to characterize and attribute sources of submicron soot particles collected in Israel during new particle formation events, biomass burning episodes, and background atmospheric conditions. Synchrotron-based X-ray microscopy was used to map soot (elemental carbon), organic carbon, and inorganic species. Implemented atomic force microscopy showed highly diverse phase states, with soot consistently exhibiting a solid-like phase. Automated µ-Raman analysis was subsequently performed on ~690 particles, identifying three soot classes based on spectral features corresponding to the "Defect" (D) and "Graphite" (G) bands of soot. We applied two-peak and five-peak fitting approaches to deconvolute the “Defect” peaks (D1, D2, D3, and D4) and G band from average Raman, revealing varying degrees of graphitic order. The degree of graphitic order was determined from metrics such as the D3 peak area, often observed when soot was internally mixed with organic material. Raman spectral features, along with temporal variations in particle classes contributions, suggest that Particle Type 1 corresponds to traffic related soot and Particle Type 2 to less graphitic soot from biomass burning, while Particle Type 3 is associated with more heterogeneous particulate representative of soot-OC mixtures emitted during new particle formation and biomass burning episodes.

Rivera-Adorno, Felipe (ORCID:0000000273557999)↗
DOE OSTI2020

A new field solver for modeling of relativistic particle-laser interactions using the particle-in-cell algorithm

A customized finite-difference field solver for the particle-in-cell (PIC) algorithm that provides higher fidelity for wave-particle interactions in intense electromagnetic waves is presented. In many problems of interest, particles with relativistic energies interact with intense electromagnetic fields that have phase velocities near the speed of light. Numerical errors can arise due to (1) dispersion errors in the phase velocity of the wave, (2) the staggering in time between the electric and magnetic fields and between particle velocity and position and (3) errors in the time derivative in the momentum advance. Errors of the first two kinds are analyzed in detail. It is shown that by using field solvers with different -space operators in Faraday’s and Ampere’s law, the dispersion errors and magnetic field time-staggering errors in the particle pusher can be simultaneously removed for electromagnetic waves moving primarily in a specific direction. Here, the new algorithm was implemented into Osiris by using customized higher-order finite-difference operators. Schemes using the proposed solver in combination with different particle pushers are compared through PIC simulation. It is shown that the use of the new algorithm, together with an analytic particle pusher (assuming constant fields over a time step), can lead to accurate modeling of the motion of a single electron in an intense laser field with normalized vector potentials, eA / mc 2 , exceeding for typical cell sizes and time steps.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Effect of particle characteristics, kinetics and transport phenomena on the prediction of particle mass loss and products yields during biomass fast pyrolysis

Here a low computational cost model for the pyrolysis of biomass anisotropic particles was used to study the effect of thermal conductivity of the particle, CRECK kinetic scheme implementation, intraparticle secondary reactions, heats of reaction, and advection on particle conversion prediction. The model considers a shrinking anisotropic cylindrical particle with biomass pseudo-components, the appearance of liquid intermediates, intra-particle mass and heat transport and secondary reactions of volatiles. The model was validated against oak and birchwood single particle experiments. More accurate predictions for mass loss evolution are found when considering the change of the particle thermal conductivity anisotropy with conversion and the temperature dependency of the thermal conductivities of the biomass and the gas phase, compared to ignoring these phenomena. The CRECK biomass pyrolysis reaction scheme provides insights into the effect of biomass composition on the evolution of the liquid intermediate phase allowing future studies about the presence of heavy compounds in the bio-oil and other phenomena such as aerosol ejection. Secondary intraparticle vapor phase reactions showed a negligible effect in volatiles conversion while heterogeneous reactions slightly overestimate its conversion. Heats of reaction and product advection are important for accurate prediction of particle mass loss.

09 BIOMASS FUELS↗
DOE OSTI2025

Isotopic analysis of Nd nanoparticles using single particle MC-ICP-MS: A comparative study with single particle-ICP-TOF-MS

Single particle - inductively coupled plasma - mass spectrometry (SP-ICP-MS) is a powerful technique for characterization of the elemental and isotopic composition of individual particles. In this work, the capabilities of the newest generation of MC-ICP-MS with acquisition rates down to 50 ms were evaluated for single particle analysis, with a focus on isotopic precision achievable on a single-particle level. Nd (NdVO 4 ) nanoparticles (~120 nm in diameter) were used as case study and were first characterized in terms of mass (respective size) and particle number concentration by SP-ICP-TOF-MS and then by SP-MC-ICP-MS for isotopic precision. For the isotopic ratio measurements, the MC-ICP-MS performance was compared to the ICP-TOF-MS and it was found that the isotope ratio precision was increased (R 2 between 0.98 and 0.99) compared to ICP-TOF-MS (R 2 between 0.88 and 0.97). The accuracy attained on a single particle level, was compared to bulk digestion followed by MC-ICP-MS analysis, and the SP-MC-ICP-MS technique was able to determine the particle population average to be <4 %, percent relative differences for the 142 Nd/ 144 Nd, 143 Nd/ 144 Nd, 145 Nd/ 144 Nd, 146 Nd/ 144 Nd, and 148 Nd/ 144 Nd ratios The detection limit for the SP-MC-ICP-MS approach was also assessed. Here, when utilizing an all Faraday-cup based detection scheme the determined LOD for the measurements was 0.2fg for Nd, per particle. Based on these results, the newest generation of MC-ICP-MS has demonstrated its utility for performing SP measurement, particularly when high precision isotopic determination is warranted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗