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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Mapping Interfacial Solution Forces that Drive Fluorescent Nanoparticle Incorporation into Crystals

Interfacial solution structure governs processes ranging from catalytic and electrochemical reactions to particle aggregation and crystallization. Here, we design bio-inspired nanocomposites by mapping interfacial forces and controlling nanoparticle incorporation during crystal growth. Our analytical model contains measured kinetic barriers for surface approaches and equilibrium binding constants with the crystal surface. We validate this model using fluorescent silica nanoparticles and calcite. Our results show that surface chemistry dictates incorporation pathways: methoxy groups are least favorable, hydroxyls reduce kinetic barriers by interacting favorably with hydration layers, carboxylates bind strongly but must overcome a kinetic barrier, and amines outperform all kinetically and thermodynamically. This framework resolves the interplay between interfacial solution structures, particle forces and dynamics, and growth kinetics, enabling predicative control of nanocomposite formation and multiplexed mixed-particle systems.

Zhang, Mingyi [Pacific Northwest National Laborato↗
DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗
DOE OSTI2020

Experimental testing of particle attrition in CSP systems at high temperature

An alternate and sustainable form of energy is CSP systems, which capture and store the sun’s energy in the form of heat. Increasing the operational temperature of CSP systems will increase the efficiency of electricity production while operating at temperatures exceeding 700 degrees Celsius also creates novel operational problems. One approach for high-temperature CSP systems is to utilize solid particles as the primary heat transfer medium. As particles flow through this system, the movement of particles creates erosion in the forms of impact, abrasion, and attrition erosion. In the real world, while all three forms of erosion will occur simultaneously, it is imperative to understand the individual effect of each erosion over the lifetime of the powerplant. Besides material erosion and long-term durability concerns, thermal cycling of the particles could also introduce changes in particle thermal performance due to alterations in particle morphology. Current research on the issue of erosion has been limited to industrial applications and does not necessarily coincide with the operating conditions in CSP systems. We focus on attrition erosion resulting from particle-to-wall and particle-to-particle interactions. Research has shown that besides material hardness affecting how fast particles break down, attrition erosion increased as the size of the particles increased due to a higher chance of collision between the particles. Particle attrition is relevant to the CSP community as it may result in material loss, change the system's thermal performance, and generation of fines which could pose an environmental hazard. In this work, we focus on developing a test set up that can isolate and measure particle attrition when subjected to conditions relevant to Gen3 CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Falling particle impact erosion testing for particle based CSP systems

CSP systems are currently being examined as an effective method for using solar energy to generate electricity. While much of this research has been conducted using molten salt as the heat transfer medium, in recent years, solid particles have been posited as a cheaper and more energy efficient heat transfer medium for use in CSP systems. Many researchers have looked into the effectiveness of solid particles as a heat transfer medium. However, a concern with the use of particles is that the falling particles will impact various components within the CSP system, such as the hopper, the heat exchanger, and the insulating material, resulting in surface erosion and damage. With repeated impacts from falling particles, material from the surfaces under impact is removed. The degree of erosion depends on whether the substrate is made of brittle or ductile material. Furthermore, factors such as particle shape, size, hardness, concentration, impact angle, particle velocity, and substrate hardness will contribute to the erosion process and determine how much and how quickly erosion will takes place in a system. Three types of erosion will be observed simultaneously: impact erosion from particle impact on receiver, particle storage, and heat exchanger walls, abrasion erosion from particle sliding motion along walls, and attrition erosion as the particles breakdown from particle-to-particle contact and particle-to-wall interactions. It is imperative to understand each of these erosions individually for a more comprehensive understanding and prediction of CSP system durability. In this work, we developed an experimental test setup capable of measuring impact erosion at conditions relevant to 1MW CSP plant. Subsequently, Impact erosion measurements were performed for three different candidate substrate materials at low particle velocities using HSP 40/70 ceramic particles.

14 SOLAR ENERGY↗
DOE OSTI2020

Design analysis of a particle-based thermal energy storage system for concentrating solar power or grid energy storage

Energy storage is becoming indispensable for expanding renewable energy integration, and it is critical to the future low-carbon energy supply. Large-capacity, grid scale energy storage can support the integration of solar and wind power and support grid resilience with the diminishing capacity of baseload fossil power plants. With the development of thermal energy storage (TES) for concentrating solar power systems, standalone TES for grid integration becomes attractive due to the declining renewable generation cost and an increasing need for energy storage. The standalone TES system introduced in this paper can play a big role in the carbon-free energy future with capacity larger than batteries and cost likely lower than other energy storage methods such as pumped storage hydropower and compressed air energy storage, both of which also have geological limitations. To this end, we describe a TES system that uses stable, inexpensive solid particles as a TES media to provide scalable, low cost energy storage. The particle-based TES has the ability to drive various thermal power cycles including conventional steam-Rankine, air Brayton turbine with combined-cycle ability, or the emerging supercritical carbon dioxide Brayton power cycle. This work describes the containment design method including a concrete silo and an internal-insulation layer for the particle-TES system. The economic analysis shows significantly low storage cost when the particle-TES is integrated with Brayton combined-cycle power generation. The paper shows the design approach of the particle-TES system and its economic potential for bulk energy storage. The advantage of the particle-TES system as a promising bulk energy storage method is its ability to economically support dispatchable renewable grid penetration for larger capacity and longer discharging hours than current battery storage technologies.

25 ENERGY STORAGE↗
DOE OSTI2022

Methods and systems for producing nanolipoprotein particles

Provided herein are methods and systems for the production of a nanolipoprotein particle (NLP) that includes a scaffold protein a membrane forming lipid and optionally a target protein. At least one of the scaffold protein and target protein can be provided through an IVT system. The membrane forming lipid, scaffold protein and optionally the target protein can be assembled for a time and under conditions that allow obtaining high yield NLPs, NPLs with an increased solubility, an NLP of a controlled size, and/or an NLP having a size predetermined to include a pre-selected target protein.

Coleman, Matthew A.↗
DOE OSTI2024

Ultra-High-Sensitivity Aerosol Spectrometer (UHSAS) Instrument Handbook

The Ultra-High-Sensitivity Aerosol Spectrometer (UHSAS) (Figure 1) is an optical-scattering, laser-based aerosol particle spectrometer system for sizing particles in the 60 to 1000 nanometer (nm) range [1–3]. The instrument counts particles in up to 100 user-specified sizing bins. The instrument’s laser illuminates particles, which scatter light. The system captures the peak light signals that are generated. These signals are used for particle sizing, since the amount of light scattered correlates strongly with particle size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High Temperature Abrasion Erosion Testing for Particle Based CSP Systems

In this work, we demonstrate an experimental setup that would allow us to individually control each variable that could influence abrasion erosion. Subsequently, Abrasion measurements were performed for three different candidate substrate materials at low particle velocities and both low and high temperatures.

14 SOLAR ENERGY↗
DOE OSTI2020

Experimental Testing of Particle Erosion and Attrition in CSP Systems

In CSP systems using solid particles for heat transfer, erosion from the falling particles can damage the system components upon impact, and from sliding against the component walls. Furthermore, the resulting attrition of particles can change the thermal performance due to alterations in particle morphology. The research on these issues has been limited to industrial applications, and don’t necessarily coincide with the operating conditions in CSP systems. In this work, we investigated the durability of the particles selected as the heat transfer media, as well as special substrate materials that are of interest as lining materials to the particle storage tanks and hoppers. Three different erosion phenomena were studied: impact, abrasion, and attrition erosion. The low-temperature experiments revealed negligible losses from attrition and abrasion erosion. Although the substrates indicated visible surface damage from impact erosion, the actual material mass loss was small even after a throughput of 500kg of particles 63 days of 1MW CSP plant operation assuming 14 hours per day of operation. Erosion is typically classified as impact, abrasion, or attrition erosion. For example, the CSP systems utilizing solid particles as heat transfer media will likely experience impact erosion on the receiver hopper and heat exchanger walls as the solid particles fall from the reservoir. Additionally, there will be sliding erosion along the receiver walls as particles move through the hopper, and lastly, there will also be attrition erosion as the particles rub against each other. The extent of erosion depends on many factors including but not limited to particle shape and size, material hardness/brittleness and ductility, and particle impact speed and angle. Mechanistic erosion equations that are available in the literature are mostly derived from data pertaining to specific experiments and therefore can’t be applied to all applications without suitable adjustments. Survey of the literature relating to particle-based receivers revealed that the most prevalent approach has been to choose low velocities to limit erosion, but to our knowledge, little effort has been put in to fully characterize erosion at the expected operating conditions. A relatively recent work investigated the erosion of wire mesh proposed for use in a particle receiver, where the results actually showed an increase in mass as oxidation occurred on the mesh surface but the work did not investigate the particle attrition rate, and the erosion rate of a solid substrate. The end goal of this work is to develop a comprehensive particle and substrate durability model that will allow a comprehensive understanding of particle-based CSP operating conditions on component durability.

14 SOLAR ENERGY↗
DOE OSTI2026

Recursive algorithm for constructing antisymmetric fermionic states in first quantization mapping

We devise a deterministic quantum algorithm to produce antisymmetric states of single-particle orbitals in the first quantization mapping. Unlike sorting-based antisymmetrization algorithms, which require ordered input states and high Clifford-gate overhead, our approach initializes the state of each particle independently. For a system of $η$ particles and $N$ single-particle states, our algorithm prepares antisymmetrized states of non-trivial localized (e.g., Hartree-Fock) orbitals using $O(η^2\sqrt{N})$ $T$-gates, outperforming alternative algorithms when $η ≲ \sqrt{N}$. To achieve such scaling, we require $O(\sqrt{N})$ dirty ancilla qubits for intermediate calculations. Knowledge of the single-particle states to be antisymmetrized can be leveraged to further improve the efficiency of the circuit, and a measurement-based variant reduces gate cost by roughly a factor of two. We show example circuits for two- and three-particle systems and discuss the generalization to an arbitrary number of particles. For a specific three-particle example, we decompose the circuit into Clifford $+T$ gates and study the impact of noise on the prepared state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Transient pattern formation in an active matter contact poisoning model

Abstract One of the most notable features in repulsive particle based active matter systems is motility-induced-phase separation (MIPS) where a dense, often crystalline phase and low density fluid coexist. Most active matter studies involve time-dependent activity; however, there are many active systems where individual particles transition from living or moving to dead or nonmotile due to lack of fuel, infection, or poisoning. Here we consider an active matter particle system at densities where MIPS does not occur. When we add a small number of infected particles that can poison other particles, rendering them nonmotile, we find a rich variety of time dependent pattern formation, including MIPS, a wetting phase, and a fragmented state formed when mobile particles plow through a nonmotile packing. We map the patterns as a function of time scaled by epidemic duration, and show that the pattern formation is robust for a wide range of poisoning rates and activity levels. We also show that pattern formation does not occur in a random death model, but requires the promotion of nucleation by contact poisoning. Our results should be relevant to biological and active matter systems where there is some form of poisoning, death, or transition to nonmotility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Application of Convolutional and Feedforward Neural Networks for Fault Detection in Particle Accelerator Power Systems

High voltage converter modulators (HVCM) provide power to the accelerating cavities of the spallation neutron source (SNS) facility. HVCM experience catastrophic failures, which increase the downtime of the SNS and reduce beam time. The faults may occur due to different reasons including failures of the resonant capacitor, core saturation due to the magnetic flux, insulated-gate bipolar transistor (IGBT) failures, and others. We recently have setup a HVCM test stand to develop and test machine learning models for anomaly detection and fault prognostics. In this work, we propose binary classifiers and autoencoder architectures based on convolutional (CNN) and feedforward neural networks (FNN) to facilitate distinguishing normal from faulty waveforms coming from the HVCM during operation. The results indicate that the CNN binary classifier is the best model among the four showing very stable performance in the training and testing sets with impressive metrics of precision and recall reaching up to 99\% with a very small uncertainty. The FNN classifier shows the least performance with a large uncertainty in its metrics. The performances of the two autoencoders based on CNN and FNN were in between, showing very good performance nonetheless.

Radaideh, Majdi↗