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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Spouted bed with venturi draft tube and method for improved gas-solid contacting

A Venturi draft tube spouted bed and method are disclosed that enables scale-up with small particles and improves heat and mass transfer by increasing material turnover rate. A Venturi-style eductor has been incorporated into the spouted bed draft tube to provide suction at the bottom of the bed to better entrain material and reduce the propensity for dead zones at the bottom of the narrow conical section.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mesoscale fractal whey protein particles derived from microscale linear-shaped protein assemblies (Part 1): Manufacturing method and particle characteristics

Whey protein isolates (WPI) are widely used in processed foods for their versatile functional properties. Modifying the structural properties of proteins by assembling them into mesoscale or microscale particles may improve their functionality and broaden their applications. This study aims to manufacture and characterize mesoscale whey protein particles (WPP) derived from WPI. Two types of WPP, WPP1 (0.05 mL/min) and WPP2 (0.25 mL/min), were prepared through a multistep approach involving liquid antisolvent (LAS) precipitation, heat treatment, and microfluidization. Liquid antisolvent precipitation was performed by injecting a 20% (wt/vol) WPI dispersion (pH 7) into an ethanol-glycerol mixture (75:25, vol/vol) under laminar flow, followed by heat treatment at 80°C for 20 min as a particle hardening step. This process produced stable fiber- and ribbon-shaped whey protein assemblies (WPA), which served as precursors to WPP. Subsequent microfluidization (150 MPa, 6 passages) reduced the size of WPA, yielding mesoscale WPP with irregular morphologies and a more uniform size distribution, as revealed by microscopy and dynamic light scattering. ζ-Potential and fluorescence labeling indicated higher surface charge and surface hydrophobicity of WPP compared with untreated WPI. The WPP showed internal mass fractal and surface fractal structures at larger length scales, analyzed using small-angle X-ray scattering. Fourier transform infrared spectroscopy demonstrated an increased fraction of intermolecular β-sheets in WPP, suggesting that hydrogen bonding contributed to their formation. Gel electrophoresis confirmed that disulfide bonds served as the primary cross-links stabilizing the WPP structure. Furthermore, turbidity measurements showed that WPP exhibited superior colloidal phase stability compared with untreated WPI and maintained high colloidal stability under both acidic and neutral pH conditions.

Antisolvent precipitation↗
DOE OSTI2024

Probing Thermal Transport in Fluidized Bed Using Modulated Photothermal Radiometry

Abstract In concentrated solar power (CSP) applications, fluidized bed is a promising approach for high heat transfer coefficient (HTC) solar receivers and heat exchangers. However, the complexity of multiphase mixing has made it difficult to characterize and analyze the heat transfer mechanism. This paper presents an experimental study on simultaneously characterizing heat transfer in both the near-wall and the bulk regions of a fluidized bed using modulated photothermal radiometry (MPR). The MPR is a non-contact frequency-domain technique using an intensity-modulated laser as the heat source and surface infrared emission as thermometry. The thermal penetration depth of the laser heating is varied by controlling its modulation frequency, and thus the measurement can resolve the near-wall and the bulk thermal resistances. With the MPR technique, we measured fluidized silica sands with a mean size of 164 μm in a vertical channel of 6 mm depth. Our results show that the near-wall thermal resistance is substantially increased with increasing gas velocity, which partially offsets the benefit of higher HTC brought by stronger particle mixing during the fluidization. We also used the MPR to quantify the improvement in particle-wall heat transfer in an inclined channel. We found that an 8° inclination towards the heat exchanging side led to a lower near-wall thermal resistance and a higher HTC at high gas velocities. This work demonstrates that the MPR technique is a useful tool to quantify the important near-wall thermal resistance from a bulk particle bed, which not only advances our understanding of heat transfer in fluidized beds, but may also contribute to the design of fluidized bed heat exchangers with higher HTC.

14 SOLAR ENERGY↗
DOE OSTI2023

Semi-supervised graph neural networks for pileup noise removal

Abstract The high instantaneous luminosity of the CERN Large Hadron Collider leads to multiple proton–proton interactions in the same or nearby bunch crossings (pileup). Advanced pileup mitigation algorithms are designed to remove this noise from pileup particles and improve the performance of crucial physics observables. This study implements a semi-supervised graph neural network for particle-level pileup noise removal, by identifying individual particles produced from pileup. The graph neural network is firstly trained on charged particles with known labels, which can be obtained from detector measurements on data or simulation, and then inferred on neutral particles for which such labels are missing. This semi-supervised approach does not depend on the neutral particle pileup label information from simulation, and thus allows us to perform training directly on experimental data. The performance of this approach is found to be consistently better than widely-used domain algorithms and comparable to the fully-supervised training using simulation truth information. The study serves as the first attempt at applying semi-supervised learning techniques to pileup mitigation, and opens up a new direction of fully data-driven machine learning pileup mitigation studies.

43 PARTICLE ACCELERATORS↗
NASA NTRS2000

DMSP SSJ4 Data Restoration, Classification, and On-Line Data Access

Compress and clean raw data file for permanent storage We have identified various error conditions/types and developed algorithms to get rid of these errors/noises, including the more complicated noise in the newer data sets. (status = 100% complete). Internet access of compacted raw data. It is now possible to access the raw data via our web site, http://www.jhuapl.edu/Aurora/index.html. The software to read and plot the compacted raw data is also available from the same web site. The users can now download the raw data, read, plot, or manipulate the data as they wish on their own computer. The users are able to access the cleaned data sets. Internet access of the color spectrograms. This task has also been completed. It is now possible to access the spectrograms from the web site mentioned above. Improve the particle precipitation region classification. The algorithm for doing this task has been developed and implemented. As a result, the accuracies improved. Now the web site routinely distributes the results of applying the new algorithm to the cleaned data set. Mark the classification region on the spectrograms. The software to mark the classification region in the spectrograms has been completed. This is also available from our web site.

Wing, Simon↗
NASA NTRS1983

Charged Particle Flux Sensor

Improved version of Faraday cup increases accuracy of measurements of flux density of charged particles incident along axis through collection aperture. Geometry of cone-and-sensing cup combination assures most particles are trapped.

Gregory, D. A.↗
NASA NTRS2003

"Hypothetical" Heavy Particles Dynamics in LES of Turbulent Dispersed Two-Phase Channel Flow

The extensive experimental study of dispersed two-phase turbulent flow in a vertical channel has been performed in Eaton's research group in the Mechanical Engineering Department at Stanford University. In Wang & Squires (1996), this study motivated the validation of LES approach with Lagrangian tracking of round particles governed by drag forces. While the computed velocity of the flow have been predicted relatively well, the computed particle velocity differed strongly from the measured one. Using Monte Carlo simulation of inter-particle collisions, the computation of Yamamoto et al. (2001) was specifically performed to model Eaton's experiment. The results of Yamamoto et al. (2001) improved the particle velocity distribution. At the same time, Vance & Squires (2002) mentioned that the stochastic simualtion of inter-particle collisions is too expensive, requiring significantly more CPU resources than one needs for the gas flow computation. Therefore, the need comes to account for the inter-particle collisions in a simpler and still effective way. To present such a model in the framework of LES/Lagrangian particle approach, and to compare the calculated results with Eaton's measurement and modeling of Yamamoto is the main objective of the present paper.

Gorokhovski, M.↗
DOE OSTI2023

Understanding the Chemomechanical Function of the Silver–Carbon Interlayer in Sheet-type All-Solid-State Lithium–Metal Batteries

All-solid-state batteries with lithium metal anodes hold great potential for high-energy battery applications. However, forming and maintaining stable solid–solid contact between the lithium anode and solid electrolyte remains a major challenge. One promising solution is the use of a silver–carbon (Ag–C) interlayer, but its chemomechanical properties and impact on interface stabilities need to be comprehensively explored. Here, we examine the function of Ag–C interlayers in addressing interfacial challenges using various cell configurations. Experiments show that the interlayer improves interfacial mechanical contact, leading to a uniform current distribution and suppressing lithium dendrite growth. Furthermore, the interlayer regulates lithium deposition in the presence of Ag particles via improved Li diffusivity. The sheet-type cells with the interlayer achieve a high energy density of 514.3 Wh L –1 and an average Coulombic efficiency of 99.97% over 500 cycles. Furthermore, this work provides insights into the benefits of using Ag–C interlayers for enhancing the performance of all-solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Improving BC Mixing State and CCN Activity Representation With Machine Learning in the Community Atmosphere Model Version 6 (CAM6)

Abstract Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non‐BC species and large mass ratio of coating to BC ( R BC , the mass ratio of non‐BC species to BC in BC‐containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle‐resolved simulations to the CAM6 with MAM4 (MAM4‐ML). In MAM4‐ML, we use R BC to partition accumulation mode particles into two new modes, BC‐free particles and BC‐containing particles. We adjust R BC to make the modeled BC mixing state index ( χ mode ) match the one predicted by the ML model ( χ ML ). On a global average, the mass fraction of BC‐containing particles in accumulation mode decreases from 100% (MAM4‐default) to 48% (MAM4‐ML). The globally averaged χ mode decreases from 78% (MAM4‐default) to 63% (MAM4‐ML, 19% reduction) and agrees well with χ ML (66%). The R BC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC‐containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Intralattice-bonded phase-engineered ultrahigh-Ni single-crystalline cathodes suppress strain evolution

Single crystallization remains a debated strategy for advancing Ni-rich cathode materials. While it mitigates particle cracking and improves tap density by eliminating particle boundaries, extended diffusion pathways introduce volumetric and lattice distortions, compromising electrochemical and structural stability. These challenges hinder the commercialization of high-Ni single-crystal cathodes, calling for a reassessment of their viability. Here, in this study, we report a structural design: intralattice-bonded phase single-crystal LiNi 0.92 Co 0.03 Mn 0.05 O 2 (IBP-SC92). This architecture maintains structural integrity while shortening diffusion pathways, resulting in almost zero electrochemical degradation during cycling. The robust structure and fast ion transport mitigate lattice strain, as confirmed by multiscale high-resolution diffraction and imaging techniques, preventing intragranular cracks and irreversible phase transitions. As a result, IBP-SC92 shows outstanding cycling stability, with nearly 100% capacity retention after 100 cycles in half cells and 94.5% retention after 1,000 cycles in full cells. This redefined single-crystal cathode represents a significant step towards the industrial adoption of high-energy-density materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗
DOE OSTI2024

Effect of post-deposition heat treatment on microstructure and mechanical properties of NASA HR-1 cold spray coatings

The primary goal of this work was to examine the impact of heat treatment on the evolution of microstructure and mechanical properties of NASA HR-1 cold spray coatings. Coatings were produced employing a high pressure cold spray system using N2 and He process gases and the effect of process gas and deposition temperature on the microstructure and mechanical properties of the coatings was examined. Microstructural characterization was performed using optical microscopy, scanning electron microscopy, micro X-ray computed tomography, and electron backscatter diffraction. NASA HR-1 coatings produced with He process gas exhibited improved plastic deformation and resulted in the lowest porosity compared to those deposited with N2 process gas. All coatings showed brittle failure with limited ductility in the as-deposited condition. Heat treatment of the NASA HR-1 cold spray coatings was performed at 550°C and 950°C for 1 h to improve the mechanical strength of the coatings. Heat treatment improved the particle bonding and enhanced the mechanical properties of the cold spray coatings. Heat treatment performed at 550°C resulted in higher mechanical strength of coatings, whereas the heat treatment performed at 950°C resulted in recrystallized microstructure and improved ductility of the coatings. However, heat treatment at 950°C resulted in forming the Eta (η) phase and Ni-Ti intermetallics in all the NASA HR-1 cold spray coatings. Here, the overall results suggest that using He as process gas contributed to reduced porosity and enhanced mechanical properties of the cold spray coatings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Anisotropic Thermally Conductive Composites Enabled by Acoustophoresis and Stereolithography

Opportunities to improve thermal management in electronic devices are currently hindered by processing constraints that limit thermal conductivity in polymer-matrix composites. Active patterning of filler particles is a promising route to improve conductivity while retaining processability by improving particle contact density and directing heat along optimized pathways. Here, we employ acoustic patterning to align and compact filler particles into stripes during stereolithographic 3D printing. This approach produces polymer-based composite materials with highly efficient embedded heat transport pathways which reach 95 vol% particle utilization (relative to the parallel conduction upper limit). These composites exhibit anisotropic thermal conductivity up to 300% higher than unpatterned composites, with in-plane anisotropy ratios of up to 350%. Combining this high conductivity with 3D printing enables materials with engineered heat networks that optimize transport from hot spots to heatsinks while maintaining low viscosity for fast particle patterning and for infiltration around electronic components. Finally, numerical simulations of acoustic assembly of particles with varied geometry, when compared to experimentally characterized particle packing, illuminate pathways for further improving conductivity by optimizing particle geometry for alignment and stacking of particles with maximum contact surface area.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Applying the Kalman filter particle method to strange and open charm hadron reconstruction in the STAR experiment

Here, we apply KF Particle, a Kalman Filter package for secondary vertex finding and fitting, to strange and open charm hadron reconstruction in heavy-ion collisions in the STAR experiment. Compared to the conventional helix swimming method used in STAR, the KF Particle method improves the reconstructed Λ, Ω and $D$ 0 significance considerably. At the same time, we demonstrate that Monte Carlo simulation with the STAR detector responses can well reproduce the topological variable distributions reconstructed in real data using the KF Particle method, therefore retaining good control on the reconstruction efficiency uncertainties for strange and open charm hadrons measurements in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

DOE Advanced Gas Reactor Fuel Development and Qualification Program

Breakdown of the DOE Advanced Gas Reactor Fuel Development and Qualification Program. Including discussion topics on TRISO technology Status Circa 2000, New Production Reactor (NPR) Fuel Experience, Fuel Qualification, US DOE Advanced Gas Reactor (AGR) Fuel Development and Qualification Program, Initial AGR Program Reference HTGR Design, Fuel Qualification Approach, Fuel Performance Modeling, Fuel Fabrication, Selected AGR-1, AGR-2, and AGR-5/6/7 Fuel Property Means, AGR Program TRISO Fuel Key Performance Data, Irradiation Performance: Fission Gas R/B, Irradiation Testing Results, Kernel and Coating Behavior During Irradiation, Locating and Studying Failed Particles Greatly Improves Understanding of Fuel Performance, Fission Product Release from UCO Fuel Compacts: AGR-1 and AGR-2 Examples, HTGR Accident Safety Testing of TRISO Fuel, Evaluating Behavior During D-LOFC Accidents, Safety Test Results for US UCO Fuel, Particle Failure Evaluation, Fuel Performance Summary, Ongoing Work and Outstanding Data Needs, Core Oxidation, Industry Engagement, and Coated-Particle-Fueled Reactor Concepts and Fuel Designs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here, we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation, and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Enhanced delivery of engineered Fe-Mn binary oxides in heterogeneous porous media for efficient arsenic stabilization

Heterogeneity in sediment and aquifer is universal, resulting in preferential flows of injected materials in the high permeability regions and forming flow by-passed zones in the low permeability regions during in-situ subsurface remediation. This adverse effect can considerably delay the completion of remedial operations and significantly increase the cost. Column experiments were designed and conducted to study the transport of starch- and starch-xanthan gum modified Fe-Mn binary oxide particles (SFM and SXFM) in saturated heterogeneous porous media and to reveal the particles’ arsenic (As) stabilization performance. Fine-in-Coarse (FIC) and Coarse-in-Fine (CIF) patterns of heterogeneous packings were set up in the columns. Testing results demonstrated that starch-xanthan gum dual treatment on Fe-Mn binary oxides successfully improved the particles’ migration capability in heterogeneous porous media and their distribution uniformity attributed to the profound shear thinning behavior of xanthan gum solution. The addition of xanthan gum to the system increased the viscosity and shear thinning property of SXFM suspension, making it a better candidate for delivery. Both SFM and SXFM stabilized As in heterogeneously packed sediment collected from a contaminated site, with SXFM showing better stabilization performance than SFM. The stabilization effects of SXFM were 90.7-97.0%, compared to 82.0-95.2% of SFM.

Yan, Xiulan↗
DOE OSTI2021

Three influential factors on colloidal nanoparticle deposition for heat conduction enhancement in 3D chip stacks

Thermal management is one of the major challenges facing the development of three-dimensional (3D) chip stacks. Recently, experimental studies have shown that neck-based thermal structure (NTS) between chip layers formed by drying of colloidal suspension in cavity filled with micro-size particles can improve the vertical heat conduction threefold. However, a deep understanding of the mechanisms of neck formation and its influence on heat conduction is still lacking. In this paper, we numerically study the effects of three parameters, i.e., initial nanoparticle concentration, drying temperature and chip surface wettability on neck formation between filler particles and on the resulting heat conduction of the NTS. With increasing nanoparticle concentration, the size and number of necks increase, resulting in an increased effective thermal conductivity (ETC) of NTS. The drying temperature is found to have only little influence on the ETC of resultant NTS, while the neck size and spatial distribution become more uniform at higher drying temperature. When reducing the wettability of the top and bottom surfaces of the cavity, the necks shrink in size until completing evacuating at the top and bottom layers, while the size of the necks between filler particles in the middle height of the cavity expands slowly. In consequence, the ETC of NTS drops at an increasing rate. Being able to reveal the underlying multiple mechanisms of two-phase flow, phase change and heat transport, the current numerical study suggests optimal values for the deposition process, with initial nanoparticle concentration over 0.8%, a drying temperature of 60°C and a uniform contact angle of 30° for practical production of NTS.

3D chip stacks↗