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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Particle trapping, size-filtering, and focusing in the nonthermal plasma synthesis of sub-10 nanometer particles

Low-pressure nonthermal flowing plasmas are widely used for the gas-phase synthesis of nanoparticles and quantum dots of materials that are difficult or impractical to synthesize using other techniques. To date, the impact of temporary electrostatic particle trapping in these plasmas has not been recognized, a process that may be leveraged to control particle properties. Furthermore, we present experimental and computational evidence that, during their growth in the plasma, sub-10 nm silicon particles become temporarily confined in an electrostatic trap in radio-frequency excited plasmas until they grow to a size at which the increasing drag force imparted by the flowing gas entrains the particles, carrying them out of the trap. We demonstrate that this trapping enables the size filtering of the synthesized particles, leading to highly monodisperse particle sizes, as well as the electrostatic focusing of the particles onto the reactor centerline. Understanding of the mechanisms and utilization of such particle trapping will enable the design of plasma processes with improved size control and the ability to grow heterostructured nanoparticles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Size-tunable silver nanoparticle synthesis in glycerol driven by a low-pressure nonthermal plasma

Silver nanoparticles (NPs) are extensively used in electronic components, chemical sensors, and disinfection applications, in which many of their properties depend on particle size. However, control over silver NP size and morphology still remains a challenge for many synthesis techniques. Here, in this work, we demonstrate the surfactant-free synthesis of silver NPs using a low-pressure inductively coupled nonthermal argon plasma. Continuously forming droplets of silver nitrate (AgNO 3 ) precursor dissolved in glycerol are exposed to the plasma, with the droplet residence time being determined by the precursor flow rate. Glycerol has rarely been studied in plasma-liquid interactions but shows favorable properties for controlled NP synthesis at low pressure. We show that the droplet residence time and plasma power have strong influence on NP properties, and that improved size control and particle monodispersity can be achieved by pulsed power operation. Silver NPs had mean diameters of 20 nm with geometric standard deviations of 1.6 under continuous wave operation, which decreased to 6 nm mean and 1.3 geometric standard deviation for pulsed power operation at 100 Hz and 20% duty cycle. We propose that solvated electrons from the plasma and vacuum ultraviolet (VUV) radiation induced electrons produced in glycerol are the main reducing agents of Ag + , the precursor for NPs, while no significant change of chemical composition of the glycerol solvent was detected.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Particle charge distributions in the effluent of a flow-through atmospheric pressure low temperature plasma

Atmospheric pressure low-temperature plasmas are often utilized to perform particle synthesis, treatment, and removal. It is well-known that dust particles are highly negatively charged in these plasmas; however, little is known about dust particle charging behavior as particles leave the plasma volume and pass through the spatial afterglow region. In this work, monodisperse particles of various sizes and work functions were introduced into an atmospheric pressure radiofrequency capacitively coupled flow-through plasma. Dust particle electrical mobility distributions downstream of the flow-through plasma were measured utilizing a differential mobility analyzer in conjunction with a condensation particle counter at various gas flow velocities. Charge distributions were determined from the measured electrical mobility distributions. Experiments confirm that particles become less negatively charged, and even net-positively charged after leaving the plasma volume, with a distribution that follows a shifted Boltzmann charge distribution. Additionally, particle charge in the effluent of the flow-through plasma is negligibly dependent on work function but highly size and flow velocity dependent. Larger particles were shown to have a higher magnitude of charge under all studied conditions; however, particle polarity was switchable by varying gas flow velocity. The charging dynamics were simulated utilizing a constant number Monte Carlo model that accounts for electron temperature decay and the transition from ambipolar to free diffusion of electrons and ions in the spatial afterglow. Simulation results also suggest that, at the same flow velocity, larger particles obtain a greater magnitude of charge, negative or positive. Furthermore, the decrease in electron mobility and the difference between ion and electron convective loss rates create an ion-rich region in the plasma effluent that promotes ion–particle collisions and drives particle charge removal and even reversal of polarity. Larger particles more favorably collide with energetic species in these environments, which results in higher charge states.

atmospheric pressure low temperature plasma↗
DOE OSTI2020

Dispersion of the Nonlinear Susceptibility of MoS2 and WS2 from Second-Harmonic Scattering Spectroscopy

Dispersion of the absolute second-order susceptibility of both MoS2 and WS2 is assessed on a wide spectral excitation range (710–1300 nm) by using second-harmonic scattering spectroscopy (SHS). SHS is an accurate ensemble measurement here applied on well-dispersed suspensions of monodisperse liquid-exfoliated nanosheets showing a high monolayer content. The as-derived, high susceptibility values shed light on the discrepancies between available literature values while evidencing resonances associated with the main excitonic transitions.

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗
DOE OSTI2020

Detecting depinning and nonequilibrium transitions with unsupervised machine learning

Using numerical simulations of a model disk system, we demonstrate that a machine learning generated order-parameter-like measure can detect depinning transitions and different dynamic flow phases in systems driven far from equilibrium. Furthermore, we specifically consider monodisperse passive disks with short range interactions undergoing a depinning phase transition when driven over quenched disorder. The machine learning derived order-parameter-like measure identifies the depinning transition as well as different dynamical regimes, such as the transition from a flowing liquid to a phase separated liquid-solid state that is not readily distinguished with traditional measures such as velocity-force curves or Voronoi tessellation. The order-parameter-like measure also shows markedly distinct behavior in the limit of high density where jamming effects occur. Our results should be general to the broad class of particle-based systems that exhibit depinning transitions and nonequilibrium phase transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Bidisperse supension balance model

The suspension balance model (SBM) for viscous Stokes flow has been well studied for the case of identical, monodisperse spherical particles in a channel, however, more work remains to be done to explore the bidisperse and polydisperse SBM. Here, we present a simple extension of the SBM that allows for modeling of suspensions of particles of bidisperse size. The comparison with avaiable experiments and direct simulations is found to be good. Additionally, we present a range of simulations to justify the assumptions made in the polydisperse suspension balance model for non-Brownian, neutrally buoyant particles that vary in size with a bidisperse distribution. The aim is to study the effects of moderate size variation on the rheology of the suspension and the distribution of the particles across the flow, especially in the near-wall regions. It is shown that, at the size ratios considered, bidispersity in the particle size does not significantly affect rheological parameters including the particle volume fraction and relative viscosity in the bulk of a Couette flow. The particle phase stresses are distributed between small and large particles in proportion to the relative volume fractions of each species. In bidisperse suspensions, the large particles in the wall layer develop a spatial structure and form chains in the streamwise direction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Emergence of Intermediate Range Order in Jammed Packings

We perform a structural analysis of large scale jammed packings of monodisperse, frictionless and frictional spheres to elucidate structural signatures of the static structure factor in the low-to-intermediate wave number region. We employ discrete element method simulations containing up to 8×10^{7} particles, in which the particle friction coefficient(s), including sliding, rolling, and twisting interactions, are varied. At intermediate wave number values, corresponding to length scales that lie between that of the nearest neighbor primary peak and the system size, we find the emergence of a prepeak-a signature of intermediate range order-that grows with increasing friction. We correlate the emergence of this peak to real space fluctuations in the local particle coordination number, which exhibits a grainy fluctuating field throughout the packing process that is retained in the final, mechanically stable state. While the formation of the prepeak shows varying degrees of robustness to packing protocol changes, our results suggest that preparation history may be used to construct packings with variable large length scale structural properties.

Monti, Joseph M↗
DOE OSTI2025

Shielded magnetic small-angle neutron scattering for characterization of radioactive samples

The development of a Pb-shielded fixture for the execution of a small-angle neutron scattering (SANS)-based workflow for interrogation of highly irradiated nuclear materials has been explored. The Pb shielding was specially designed to reduce the detected radioactivity from the specimen during SANS experiments, and the overall configuration is termed shielded magnetic SANS (SM-SANS). Two FeCrAl-based alloys, C35M and 125YF, were examined with the SM-SANS technique using a free-form size distribution locally monodisperse model in both the as-received and irradiated states. Quantitative values derived from the free-form size distribution were compared with atom probe tomography experiments. Microstructural and compositional parameters determined using the two characterization techniques were complements of each other. The results demonstrate that the SM-SANS technique is an effective means of characterizing nanoscale clustering in irradiated material systems and provides new avenues for investigating radioactive material microstructures.

FeCrAl↗
DOE OSTI2025

Machine-learning-informed scattering correlation analysis of sheared colloids

We have carried out theoretical analysis, Monte Carlo simulations and machine-learning analysis to quantify microscopic rearrangements of dilute dispersions of spherical colloidal particles from coherent scattering intensity. Both monodisperse and polydisperse dispersions of colloids were created and underwent a rearrangement consisting of an affine simple shear and non-affine rearrangement using the Monte Carlo method. We calculated the coherent scattering intensity of the dispersions and the correlation function of intensity before and after the rearrangement and generated a large data set of angular correlation functions for varying system parameters, including number density, polydispersity, shear strain and non-affine rearrangement. Singular value decomposition of the data set shows the feasibility of machine-learning inversion from the correlation function for the polydispersity, shear strain and non-affine rearrangement using only three parameters. A Gaussian process regressor is then trained on the data set and can retrieve the affine shear strain, non-affine rearrangement and polydispersity with relative errors of 3%, 1% and 6%, respectively. Altogether, our model provides a framework for quantitative studies of both steady and non-steady microscopic dynamics of colloidal dispersions using coherent scattering methods.

Gaussian process regression↗
DOE OSTI2024

Two-Fluid and Discrete Element Modeling of a Parallel Plate Fluidized Bed Heat Exchanger for Concentrating Solar Power

A novel high-temperature particle solar receiver is developed using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a fluidized bed at the lower section, leaving the system from the bottom at a constant flowrate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built by collaborators at the Colorado School of Mines and their data are used for model validation. In this experimental setup, near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using the discrete element method and a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A new continuum conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2 K.

concentrating solar power↗
DOE OSTI2023

Multiphase Modeling in a Parallel Plate Fluidized Bed Receiver for Concentrating Solar Power

A novel high temperature particle solar receiver is developed by using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a packed bed at the lower end, leaving the system from the bottom at a constant flow rate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built and a near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2K.

CSP↗
DOE OSTI2020

Imaging Cycle-Induced Damage of MnO 2 Microparticles

MnO 2 has been proposed as an electrode material in electrochemical energy storage devices. However, poor cycle life, especially in aqueous electrolytes, remains a detriment to commercialization. Prior studies have suggested a number of explanations for this capacity loss; however, experiments aimed at elucidating the details of the degradation process (es) are sparse. We describe here a microtube-membrane construct that allows for electrodeposition of monodisperse MnO 2 microparticles distributed across the membrane surface, and for subsequent electrochemical cycling of these MnO 2 particles. This allowed for a detailed analysis of the effect of cycling on the MnO 2 , by simply imaging the membrane surface before and after cycling. When an aqueous electrolyte was used, gross changes in particle shape, size and morphology were observed over the course of 500 cycles. Partial dissolution occurred as well. No such changes were observed when the MnO 2 particles were cycled (up to 500 times) in a propylene carbonate electrolyte solution.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Oxygen Evolution on Iron Oxide Nanoparticles: The Impact of Crystallinity and Size on the Overpotential

The oxygen evolution reaction (OER) is a critical reaction in electrolysis and photoelectrolysis of water to generate and store clean energy. Therefore, the development of low-cost and efficient electrocatalysts for the OER is of great scientific and technological importance. Although promising iron oxide-based electrocatalysts have been recently developed for the OER, an in-depth experimental and theoretical analysis of the OER mechanism on iron oxide-based electrocatalysts is still needed to provide guidelines to optimize the performance of iron oxide-based electrocatalysts further. To address this need, we synthesized a series of monodisperse iron oxide nanoparticles to analyze their intrinsic OER activities. Using nanoparticles of the same size but different crystallinity, we show that amorphous iron oxide nanoparticles have better OER activity than crystalline ones. The size effect studies further revealed that the edge/defect sites are the active sites for the OER. Density functional theory calculations demonstrated that the edge/defect sites provide bridge sites to adsorb OER intermediates, resulting in low OER overpotential. These calculations confirm that the high OER activity of amorphous nanoparticles results from a high concentration of defect sites on their surface. These results provide novel strategies to increase the performance of iron oxide-based and likely other oxide-based OER electrocatalysts.

Electrochemistry↗
DOE OSTI2022

New Empirical Formulation for the Sublimational Breakup of Graupel and Dendritic Snow

Abstract Ice fragments are generated by sublimation of ice particles in subsaturated conditions in natural clouds. Conceivably, such sublimational breakup would be expected to cause ice multiplication in natural clouds. Any fragment that survives will grow to become ice precipitation that may sublimate and fragment further. As a first step toward assessing this overlooked process, a formulation is proposed for the number of ice fragments from sublimation of ice particles for an atmospheric model. This is done by amalgamating laboratory observations from previously published studies. The concept of a “sublimated mass activity spectrum” for the breakup is applied to the dataset. The number of ice fragments is determined by the relative humidity over ice and the initial size of the parent ice particles. The new formulation applies to dendritic crystals and heavily rimed particles only. Finally, a thought experiment is performed for an idealized scenario of subsaturation with in-cloud descent. Scaling analysis yields an estimate of an ice enhancement ratio of about 5 (10) within a weak deep convective downdraft of about 2 m s −1 , for an initial monodisperse population of dendritic snow (graupel) particles of 3 L −1 and 2 mm. During descent, there is a dynamic equilibrium between continual emission of fragments and their depletion by sublimation. A simplified bin microphysics parcel model exhibits this dynamical quasi equilibrium, consistent with the thought experiment. The fragments have average lifetimes of around 90 and 70 s for dendrites and graupel, respectively. Sublimational breakup is predicted to cause significant secondary ice production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Effect of Plutonium on Uranium Oxide Microstructural Fingerprint

The analysis of particulates from environmental sampling is routinely performed for nuclear forensics applications. In order to increase the tools available for nuclear forensics applications, capability development materials (CDMs), or reference particulates, are necessary for developing and benchmarking new analytical methods. Historically, these CDM particulates have been produced with highly controlled and characterized isotopic and size parameters for applications in developing and benchmarking particle sizers and mass spectrometry analytical methods [1- 4]. However, the development of CDMs with highly characterized particle morphology and phase of the particles is vital for aiding in the development and benchmarking of particle analytical methods for those parameters. In many cases, key properties such as crystallographic phase, morphology, and microstructure, may be correlated to processing history of environmental sampling particulates [5]. To that end, this work investigates determining the structural fingerprint of produced Pu-doped uranium oxide CDMs using transmission electron microscopy (TEM). The particulates, one of which shown in Figure 1, were synthesized to Fig. 1. Single particulate of uranium oxide fabricated using the THESEUS technique. develop capabilities for environmental sampling investigations. These particles are monodisperse at diameter of 1 μm and a range of plutonium concentrations from 0- 1,000 ppm. Given their small diameter, TEM analysis was ideal for studying the particulate structural fingerprint in detail. Previous investigations confirmed the external homogeneity of the particulates at different plutonium concentrations, however this analysis focuses on determining the grain structure, phase distribution, and porosity of the particulates.

Mayer, Jack [Univ. of Florida, Gainesville, FL (Un↗
DOE OSTI2020

Computational Fluid Dynamics Analysis of a 12 MW Circulating Fluidized Bed Rise

A three-dimensional (3D) two fluid model (TFM) model of the 12 MW circulating fluidized bed (CFB) riser at Chalmers University was developed using the open-source Multiphase Flow with Interphase eXchanges (MFiX) Software Suite. The hydrodynamic behavior of the riser was validated by comparing axial pressure profiles from experimental measurements with the results from the simulations. Under some of the operating conditions where there was no external circulation of solids, the pressure profiles from the simulation matched well with the experimental measurements. For the cases where there was external circulation of solids, the pressure profiles with the monodisperse solid phase modeling underpredicted the solids concentration in the freeboard region. With the inclusion of polydispersity in the model, the predicted pressure profiles agreed well with the experimental measurements. A two-dimensional (2D) model of the riser was used to perform simulations of coal combustion. The predicted flue gas outlet compositions of oxygen and carbon dioxide compared reasonably to experiments. The experiments also reported some concentration of carbon monoxide which was overpredicted in the simulations. Additional experimental data such as axial oxygen concentration profile and pressure profiles were also compared with the experiment. It was observed that the oxygen concentration in the bottom bed from the simulations was higher than in the experiments, which suggested that most of the oxidation reactions occurred in the bottom bed. The concentration of volatiles and char in the simulations was lower in the bottom bed than in the experiments, which suggest that there is not sufficient penetration of the solid phase species into the bed.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Self-Assembly of Virus Particle Based Materials for Hydrogen Catalysis

Viruses are sophisticated protein-based containers and their self-assembly from a small number of subunits into symmetrical, monodisperse architectures has inspired the work performed under this award. We have taken advantage of the robust self-assembly of the bacteriophage P22 for the encapsulation of enzymatic cargo materials and studied their activity in energy harvesting systems. The large internal cavity of the P22 is ideal for high-capacity loading of enzymes resulting in very high local catalyst concentrations. We have exploited the self-assembly properties of the bacteriophage P22 system for the packaging of a number of different enzymes, including a [NiFe] hydrogenase as well as enzymes capable of butanol biosynthesis, to create active and stable individual “nano-reactors”. Individual viral capsid-based nanoreactors are also ideal building blocks for the construction of higher order assemblies. We have demonstrated the construction of ordered 3-D arrays from active nanoparticle building blocks to form materials with collective behavior and properties beyond those of the individual particles and capable of catalyzing multi-step reactions. The successful implementation of the work performed under this DOE grant provides us with a great deal of knowledge about directed self-assembly at multiple lengthscales for the development of bioinspired catalytic materials for energy harvesting.

08 HYDROGEN↗